EP4655685A1 - Systems and methods for automated chemistry, manufacturing, and controls (cmc) management - Google Patents

Abstract

Presented herein are systems and methods for automated data management for the development and/or production of a pharmaceutical product. In certain embodiments, the automated data management systems and methods provide for automated chemistry, manufacturing, and controls (CMC) management.

Description

SYSTEMS AND METHODS FOR AUTOMATED CHEMISTRY, MANUFACTURING, AND CONTROLS (CMC) MANAGEMENT

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to and benefit of U.S. Provisional Application No. 63/441,121, filed January 25, 2023 and U.S. Provisional Application No. 63/453,920, filed March 22, 2023, the content of each of which is hereby incorporated by reference in its entirety.

FIELD

[0002] This invention relates generally to data management systems and methods. More particularly, in certain embodiments, the invention relates to systems and methods of enterprise data management in the development and/or production of a pharmaceutical product.

BACKGROUND

[0003] Chemistry, manufacturing, and controls (CMC) refers to activities performed in the development and manufacturing of a drug product. CMC includes activities performed at all stages of the drug development cycle to ensure quality and consistency of a manufactured pharmaceutical product, in compliance with regulatory guidance. CMC applies to both the drug product and the manufacturing facility and provides continuity between the drug used in clinical studies and the drug that is marketed commercially and made available to consumers. For example, CMC applies to the manufacturing process for the drug, quality control, specifications of the drug product, and stability of the drug product, as well as the design, qualification, operation, and maintenance of the drug product manufacturing facility.

[0004] Various database management systems exist for process development and control. However CMC, particularly for the manufacture and development of cell therapies, presents significant challenges that render current database management systems inadequate. Cell therapy manufacturing and clinical studies involve large amounts of data that need to be rapidly analyzed to drive insights - for example, the database management system should provide real-time process visualization and trending. Manufacturing of cell therapies involves many unit operations that produce large amounts of data over a variety of instruments that are automated and digitized. All this data needs to be integrated in a coherent manner.

[0005] There is a need for more advanced database management systems particularly suited for management of the kinds of heterogeneous, structured data generated by drug manufacturers, particularly cellular and tissue therapeutics such as CAR T cell therapy and allogeneic transplants, as well as other biologies (e.g., blood components, nucleic acid-based therapies such as RNAi, gene therapy, and gene editing, and the like).

SUMMARY

[0006] Presented herein are systems and methods for automated data management for the development and/or production of a pharmaceutical product. Non-limiting examples of such pharmaceutical products including, for example, a cellular therapy product such as Natural Killer (NK) cells, T cells, iPS-derived CAR T cells, Gamma-Delta (GD) T cells, or stem cells. In certain embodiments, the automated data management systems and methods provide for automated chemistry, manufacturing, and controls (CMC) management.

[0007] In one aspect, the invention is directed to a method of using heterogeneous, structured data of an enterprise in the development and/or production of a pharmaceutical product (e.g., a cellular therapy product, e.g., Natural Killer (NK) cells, T cells, iPS-derived CAR T cells, Gamma-Delta (GD) T cells, or stem cells), the method comprising: (a) receiving, by a processor of a computing device, a user query via a portal (e.g., a web-based portal), said query related to one or more of the following: (i) the design of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product), (ii) the operation of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product) (e.g., process monitoring and/or process control), and (iii) the modeling of a manufacturing process for production of the pharmaceutical product (e.g., the cell therapy product); (b) conveying the user query to a mediator of a view-based data integration system (VDIS) to produce a response to the user query, wherein the VDIS accesses (e.g., via a federated server) multiple data sources with heterogeneous data formats and retrieves integrated results (e.g., combining data from multiple sources and resolving one or more inconsistencies), wherein the response to the user query comprises the integrated results; and (c) graphically rendering the response to the user query. In other embodiments, an alternative to VDIS may be used, for example, a vertical integration system and/or extract transform load (ETL) tool(s).

[0008] In certain embodiments, the multiple data sources accessed by the VDIS comprises one or more of the following: (i) raw exploratory oncology and/or cellular therapy data, (ii) processed exploratory oncology and/or cellular therapy data (e.g., results), (iii) cellular therapy product characteristics, (iv) raw pharmacokinetics data, (v) raw primary and/or secondary biologic endpoint data, (vi) manufacturing process protocols, (vii) manufacturing unit operations (device) data, and (viii) analytical device data.

[0009] In certain embodiments, step (c) comprises updating a process monitoring graphical display (e.g., monitoring dashboard) with the response to the user query in real-time (e.g., near real-time).

[0010] In certain embodiments, the multiple data sources accessed by the VDIS comprise live data (e.g., data that is updated in real-time).

[0011] In certain embodiments, step (c) comprises graphically rendering a digital page comprising multiple sentences and/or paragraphs of text, said digital page also comprising user-interactive data (e.g., tiled data) related to said text, said data updated to reflect the response to the user query [e.g., clinical interactive “stories” for communication and training].

[0012] In certain embodiments, the view-based data integration system comprises a both-as-view (BAV) [aka global and local as view (GLAV)] back-end infrastructure.

[0013] In certain embodiments, the view-based data integration system comprises a global-as-view (GAV) back-end infrastructure and/or a local-as-view (LAV) back-end infrastructure.

[0014] In certain embodiments, the mediator converts the user query into a plurality of source-specific queries and sends the source-specific queries to one or more wrappers for execution, producing the response to the query.

[0015] In certain embodiments, the back-end infrastructure comprises a plurality of sources comprising heterogeneous structured data that are integrated into a unified view. [0016] In certain embodiments, the method uses a graph-based, real-time digitalization and contextualization engine.

[0017] In certain embodiments, the multiple data sources with heterogeneous data formats accessed by the VDIS comprises at least one data source whose data is automatically harmonized at point of data collection. In certain embodiments, the at least one data source has its data automatically harmonized by restricting data entry to a plurality of predetermined fields and/or values.

[0018] In certain embodiments, step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., a process director display) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a step in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the process step represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS.

[0019] In certain embodiments, step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., a process designer) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a unit operation in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS, wherein the one or more blocks may be linked together in the creation of a new experimental and/or manufacturing process comprising the plurality of unit operations represented by the linked blocks, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the unit operation represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS. [0020] In certain embodiments, step (c) comprises graphically rendering the response to the query via a graphical user interface (e.g., patient tiles) comprising a plurality of tiles (e.g., a type of graphical widget), wherein each tile represents a particular subject (e.g., a patient in a clinical trial) whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS (e.g., wherein the tiles have different colors, shading, line-styles, or the like to visually convey data pertaining to the subjects, e.g., to convey clinical response), wherein the one or more tiles are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch- screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the subject represented by the particular tile, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS.

[0021] In certain embodiments, step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., substantially as rendered in FIGS. 4A to 34J).

[0022] In another aspect, the invention is directed to a method of using data of an enterprise in the development and/or production of a pharmaceutical product (e.g., a cellular therapy product, e.g., Natural Killer (NK) cells, T cells, iPS-derived CAR T cells, Gamma- Delta (GD) T cells, or stem cells), the method comprising: (a) receiving, by a processor of a computing device, a user query via a portal (e.g., a web-based portal), said query related to one or more of the following: (i) the design of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product), (ii) the operation of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product) (e.g., process monitoring and/or process control), and (iii) the modeling of a manufacturing process for production of the pharmaceutical product (e.g., the cell therapy product); (b) conveying the user query to a database management system to produce a response to the user query, wherein the database management system accesses (e.g., via a federated server) multiple data sources and retrieves results (e.g., combining data from multiple sources and resolving one or more inconsistencies to produce integrated results), wherein the response to the user query comprises the results; and (c) graphically rendering the response to the user query, wherein the multiple data sources accessed by the database management system comprise at least one data source whose data is automatically harmonized at point of data collection by restriction of data entry to a plurality of predetermined fields and/or values.

[0023] In certain embodiments, the multiple data sources accessed by the database management system comprises one or more of the following: (i) raw exploratory oncology and/or cellular therapy data, (ii) processed exploratory oncology and/or cellular therapy data (e.g., results), (iii) cellular therapy product characteristics, (iv) raw pharmacokinetics data, (v) raw primary and/or secondary biologic endpoint data, (vi) manufacturing process protocols, (vii) manufacturing unit operations (device) data, and (viii) analytical device data.

[0024] In certain embodiments, step (c) comprises updating a process monitoring graphical display (e.g., monitoring dashboard) with the response to the user query in real-time (e.g., near real-time).

[0025] In certain embodiments, the multiple data sources accessed by the database management system comprise live data (e.g., data that is updated in real-time).

[0026] In certain embodiments, step (c) comprises graphically rendering a digital page comprising multiple sentences and/or paragraphs of text, said digital page also comprising user-interactive data (e.g., tiled data) related to said text, said data updated to reflect the response to the user query [e.g., clinical interactive “stories” for communication and training].

[0027] In certain embodiments, the method uses a graph-based, real-time digitalization and contextualization engine.

[0028] In certain embodiments, step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., a process director display) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a step in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch- screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the process step represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system.

[0029] In certain embodiments, step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., a process designer) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a unit operation in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system, wherein the one or more blocks may be linked together in the creation of a new experimental and/or manufacturing process comprising the plurality of unit operations represented by the linked blocks, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the unit operation represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system.

[0030] In certain embodiments, step (c) comprises graphically rendering the response to the query via a graphical user interface (e.g., patient tiles) comprising a plurality of tiles (e.g., a type of graphical widget), wherein each tile represents a particular subject (e.g., a patient in a clinical trial) whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system (e.g., wherein the tiles have different colors, shading, line-styles, or the like to visually convey data pertaining to the subjects, e.g., to convey clinical response), wherein the one or more tiles are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the subject represented by the particular tile, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system. [0031] In certain embodiments, step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., substantially as rendered in FIGS. 4A to 34J).

[0032] In another aspect, the invention is directed to a system for using heterogeneous, structured data of an enterprise in the development and/or production of a pharmaceutical product (e.g., a cellular therapy product, e.g., Natural Killer (NK) cells, T cells, iPS-derived CAR T cells, Gamma-Delta (GD) T cells, or stem cells), the system comprising: a processor of a computing device; and a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to: (a) receive a user query via a portal (e.g., a web-based portal), said query related to one or more of the following: (i) the design of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product), (ii) the operation of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product) (e.g., process monitoring and/or process control), and (iii) the modeling of a manufacturing process for production of the pharmaceutical product (e.g., the cell therapy product); (b) convey the user query to a mediator of a view-based data integration system (VDIS) to produce a response to the user query, wherein the VDIS accesses (e.g., via a federated server) multiple data sources with heterogeneous data formats and retrieves integrated results (e.g., combining data from multiple sources and resolving one or more inconsistencies), wherein the response to the user query comprises the integrated results; and (c) graphically render the response to the user query. In other embodiments, an alternative to VDIS may be used, for example, a vertical integration system and/or extract transform load (ETL) tool(s).

[0033] In certain embodiments, the multiple data sources accessed by the VDIS comprises one or more of the following: (i) raw exploratory oncology and/or cellular therapy data, (ii) processed exploratory oncology and/or cellular therapy data (e.g., results), (iii) cellular therapy product characteristics, (iv) raw pharmacokinetics data, (v) raw primary and/or secondary biologic endpoint data, (vi) manufacturing process protocols, (vii) manufacturing unit operations (device) data, and (viii) analytical device data. [0034] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) update a process monitoring graphical display (e.g., monitoring dashboard) with the response to the user query in real-time (e.g., near real-time).

[0035] In certain embodiments, the multiple data sources accessed by the VDIS comprise live data (e.g., data that is updated in real-time).

[0036] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render a digital page comprising multiple sentences and/or paragraphs of text, said digital page also comprising user-interactive data (e.g., tiled data) related to said text, said data updated to reflect the response to the user query [e.g., clinical interactive “stories” for communication and training].

[0037] In certain embodiments, the view-based data integration system comprises a both-as-view (BAV) [aka global and local as view (GLAV)] back-end infrastructure.

[0038] In certain embodiments, the view-based data integration system comprises a global-as-view (GAV) back-end infrastructure and/or a local-as-view (LAV) back-end infrastructure.

[0039] In certain embodiments, the mediator converts the user query into a plurality of source-specific queries and sends the source-specific queries to one or more wrappers for execution, producing the response to the query.

[0040] In certain embodiments, the back-end infrastructure comprises a plurality of sources comprising heterogeneous structured data that are integrated into a unified view.

[0041] In certain embodiments, the system uses a graph-based, real-time digitalization and contextualization engine.

[0042] In certain embodiments, the multiple data sources with heterogeneous data formats accessed by the VDIS comprises at least one data source whose data is automatically harmonized at point of data collection. In certain embodiments, the at least one data source has its data automatically harmonized by restricting data entry to a plurality of predetermined fields and/or values. [0043] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., a process director display) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a step in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the process step represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS.

[0044] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., a process designer) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a unit operation in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS, wherein the one or more blocks may be linked together in the creation of a new experimental and/or manufacturing process comprising the plurality of unit operations represented by the linked blocks, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the unit operation represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS.

[0045] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the query via a graphical user interface (e.g., patient tiles) comprising a plurality of tiles (e.g., a type of graphical widget), wherein each tile represents a particular subject (e.g., a patient in a clinical trial) whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS (e.g., wherein the tiles have different colors, shading, line-styles, or the like to visually convey data pertaining to the subjects, e.g., to convey clinical response), wherein the one or more tiles are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the subject represented by the particular tile, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS.

[0046] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., substantially as rendered in FIGS. 4A to 34J).

[0047] In another aspect, the invention is directed to a system of using data of an enterprise in the development and/or production of a pharmaceutical product (e.g., a cellular therapy product, e.g., Natural Killer (NK) cells, T cells, iPS-derived CAR T cells, Gamma- Delta (GD) T cells, or stem cells), the system comprising: a processor of a computing device; and a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to: (a) receive a user query via a portal (e.g., a web-based portal), said query related to one or more of the following: (i) the design of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product), (ii) the operation of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product) (e.g., process monitoring and/or process control), and (iii) the modeling of a manufacturing process for production of the pharmaceutical product (e.g., the cell therapy product); (b) convey the user query to a database management system to produce a response to the user query, wherein the database management system accesses (e.g., via a federated server) multiple data sources and retrieves results (e.g., combining data from multiple sources and resolving one or more inconsistencies to produce integrated results), wherein the response to the user query comprises the results; and (c) graphically render the response to the user query, wherein the multiple data sources accessed by the database management system comprise at least one data source whose data is automatically harmonized at point of data collection by restriction of data entry to a plurality of predetermined fields and/or values. [0048] In certain embodiments, the multiple data sources accessed by the database management system comprises one or more of the following: (i) raw exploratory oncology and/or cellular therapy data, (ii) processed exploratory oncology and/or cellular therapy data (e.g., results), (iii) cellular therapy product characteristics, (iv) raw pharmacokinetics data, (v) raw primary and/or secondary biologic endpoint data, (vi) manufacturing process protocols, (vii) manufacturing unit operations (device) data, and (viii) analytical device data.

[0049] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) update a process monitoring graphical display (e.g., monitoring dashboard) with the response to the user query in real-time (e.g., near real-time).

[0050] In certain embodiments, the multiple data sources accessed by the database management system comprise live data (e.g., data that is updated in real-time).

[0051] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render a digital page comprising multiple sentences and/or paragraphs of text, said digital page also comprising user-interactive data (e.g., tiled data) related to said text, said data updated to reflect the response to the user query [e.g., clinical interactive “stories” for communication and training].

[0052] In certain embodiments, the system uses a graph-based, real-time digitalization and contextualization engine.

[0053] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., a process director display) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a step in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the process step represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system. [0054] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., a process designer) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a unit operation in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system, wherein the one or more blocks may be linked together in the creation of a new experimental and/or manufacturing process comprising the plurality of unit operations represented by the linked blocks, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the unit operation represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system.

[0055] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the query via a graphical user interface (e.g., patient tiles) comprising a plurality of tiles (e.g., a type of graphical widget), wherein each tile represents a particular subject (e.g., a patient in a clinical trial) whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system (e.g., wherein the tiles have different colors, shading, line-styles, or the like to visually convey data pertaining to the subjects, e.g., to convey clinical response), wherein the one or more tiles are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch- screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the subject represented by the particular tile, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system.

[0056] In certain embodiments, the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., substantially as rendered in FIGS. 4A to 34J). [0057] In another aspect, the invention is directed to a method for facilitating user management of manufacturing processes (e.g., experimental (e.g., lab or pilot scale) processes, developed for/in the design of a manufacturing process; e.g., commercial scale production processes) for production of pharmaceutical products (e.g., cellular therapy products, e.g., biologic drugs) via an interactive manufacturing management graphical user- interface (GUI), the method comprising: (a) receiving and/or accessing, by a processor of a computing device, manufacturing process data corresponding to a plurality of unit operations in a particular manufacturing process, said data representing (i) actions performed in the plurality of unit operations and/or (ii) information collected for the plurality of unit operations (e.g., information collected before, during, and/or after one or more of the plurality of unit operations is/are performed); and causing, by the processor, rendering of a graph- based visualization of the particular manufacturing process via the manufacturing management GUI, wherein the graph-based visualization comprises a plurality of interactive nodes [e.g., graphical icons, such as (e.g., color-coded) inter-connected circular icons], each interactive node of the plurality of interactive nodes representing (i) an individual datapoint corresponding to a particular action that is performed in one of the plurality of unit operations and/or (ii) a particular set of information that is collected for a particular one of the plurality of unit operations (e.g., information collected before, during, and/or after the particular unit operation) [e.g., wherein one or more of the interactive nodes are linked (e.g., connected with each other), each link between a first and second interactive node representing a dependency and/or sequence of material and/or data flow (e.g., each link graphically rendered as a line connecting two graphical icons representing nodes)].

[0058] In certain embodiments, the graph-based visualization comprises a timeline depicting days (e.g., over which the particular manufacturing process is performed) and/or unit operations (e.g., of the particular manufacturing process) [e.g., a vertical or horizontal line, with (e.g., labeled) markings along the line representing days and/or unit operations] and each interactive node of the plurality of interactive nodes is visually associated with a particular one of the days and/or unit operations of the timeline (e.g., positioned, within the graph-based visualization, in proximity to the particular day and/or unit operation, along a same horizonal and/or vertical axis as the particular day and/or unit operation, etc.). [0059] In certain embodiments, the graph-based visualization comprises a base graph corresponding to and representing a baseline version of the manufacturing process along with one or more auxiliary sub-graphs, each sub-graph corresponding to and representing a variation to experimental conditions and/or the baseline version of the manufacturing process [e.g., wherein the one or more auxiliary sub-graphs are displayed below the base graph (e.g., each auxiliary sub-graph comprising one or more icons representing nodes and connecting lines representing links between nodes, representing, in turn, unit operations and material and/or dataflow between them, respectively)].

[0060] In certain embodiments, the plurality of interactive nodes are dynamic such that upon a user interaction with a particular interactive node (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the datapoint represented by the particular interactive node (e.g., wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS).

[0061] In certain embodiments, the method comprises rendering, for each of one or more data parameters and/or variables being controlled and/or monitored during the particular manufacturing process, a plurality of datapoint indicators, each datapoint indicator representing a collected and/or input value of the data parameter and/or variable at a particular time point and/or unit operation during the particular manufacturing process.

[0062] In certain embodiments, the plurality of datapoint indicators are color-coded according to whether data are collected, missing, and/or selected for further analysis.

[0063] In certain embodiments, the method comprises: receiving, by the processor, via the GUI, a user selection of at least a portion of the datapoints (e.g., via a user click); and generating, by the processor, an interactive graph plotting values of the selected datapoints.

[0064] In certain embodiments, the manufacturing process data comprises a plurality of sets of values for the one or more data parameters and/or variables being controlled and/or monitored during the particular manufacturing process, each set of values associated with a distinct lot and/or batch, and wherein the interactive graph comprises a plurality of traces [e.g., lines, collections of points (e.g., as in a scatter plot), series of bars (e.g., as in a bar graph), graphical icons (e.g., as in a pictogram), etc.; e.g., as shown in any one of FIGs. 20A- 28F], each trace corresponding to and showing progression of the set of values for the particular lot and/or batch with which the set is associated.

[0065] In certain embodiments, the method comprises: receiving and/or accessing, by the processor, additional manufacturing process data corresponding to one or more additional manufacturing processes; and causing, by the processor, rendering of one or more additional graph-based visualizations, each representing a particular one of the one or more additional manufacturing processes within the manufacturing management GUI, wherein the one or more additional graph-based visualizations are aligned and/or overlaid with the graph-based visualization corresponding the particular manufacturing processes.

[0066] In certain embodiments, rendering the one or more additional graph-based visualizations comprises automatically highlighting deviations between the one or more processes and/or from a reference (e.g., visually rendering nodes and/or lines connecting them that represent unit operations having one or more parameters and/or collected data that (i) differ from those of other processes and/or (ii) deviate from reference values and/or ranges of reference values).

[0067] In certain embodiments, the method comprises generating and outputting a harmonized dataset [e.g., identifying (e.g., automatically and/or based on user input and/or selection) data points that are consistent and/or outliers, and then extracting a portion of the data points (e.g., those identified as consistent) to generate the harmonized dataset] corresponding to the particular manufacturing process and the one or more additional manufacturing processes (e.g., for subsequent mathematical modelling).

[0068] In certain embodiments, the method comprises: receiving, by the processor, via the manufacturing management GUI a user selection of one or more nodes for inclusion in a harmonized dataset and/or a user input of data into one or more nodes of the graph-based visualization and/or the one or more additional graph-based visualizations; generating, by the processor, based at least in part on the user selection and/or input of data, a harmonized dataset (e.g., a dataset in which the user selected nodes and/or initially stored data is replaced with the user input).

[0069] In another aspect, the invention is directed to a method for facilitating experimental process design and data collection for manufacturing production processes via an interactive GUI, the method comprising: (a) receiving and/or accessing, by a processor of a computing device, manufacturing process data corresponding to a particular manufacturing process and representing actions (e.g., unit operations in the particular manufacturing process) performed and/or information collected during the particular manufacturing process; (b) causing, by the processor, graphical rendering of one or more interactive panels representing the actions and/or information collected during the manufacturing processes, the one or more interactive sub-panels comprising one or more (e.g., up to all) of the following: (i) a real-time data display panel comprising graphical rendering of data obtained from and/or input to one or more connected devices used (e.g., to perform unit operations and/or collect measurements) during the particular manufacturing process; (ii) a process design display panel comprising a graphical rendering of one or more unit operations performed during the manufacturing processes (e.g., as linked tiles); (iii) a data input and calculations panel comprising a graphical rendering of a plurality of fields (e.g., textual input boxes) for input of raw data and corresponding calculations; and (iv) a material preparation and data calculations panel comprising a graphical rendering of a plurality of input fields and/or output calculations corresponding to material preparation inputs and calculations.

[0070] In certain embodiments, the unit operation comprises causing graphical rendering of the real-time data display panel and dynamically updating the real-time data display panel according to variations in values of parameters input to and/or collected from one or more interconnected devices.

[0071] In certain embodiments, step (b) comprises: causing, by the processor, graphical rendering of the process design panel, said process design panel comprising one or more selectable icons (e.g., linked tiles), each representing a particular unit operation in the manufacturing process; receiving, by the processor, a user selection of a particular unit operation for data review and/or input via a user interaction with a corresponding one of the one or more selectable icons within the process design panel; and causing, by the processor, updating, so as to reflect data associated with (e.g., collected during and/or input to) the particular unit operation, of one or more of: the real time data display panel, the data input and calculations panel, and the material preparation and data calculations panel [e.g., wherein the updating comprises identifying, within one or more databases (e.g., a knowledge base), a set of data related to the particular unit operation (e.g., and the particular manufacturing process) based on a stored ontology that links unit operations, manufacturing processes, input parameters, and collected data in a relational fashion (e.g., in a hierarchical fashion, e.g., via a knowledge graph)].

[0072] In another aspect, the invention is directed to a system for facilitating user management of manufacturing processes (e.g., experimental (e.g., lab or pilot scale) processes, developed for/in the design of a manufacturing process; e.g., commercial scale production processes) for production of pharmaceutical products (e.g., cellular therapy products, e.g., biologic drugs) via an interactive manufacturing management graphical user- interface (GUI), the system comprising: a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to: (a) receive and/or access manufacturing process data corresponding to a plurality of unit operations in a particular manufacturing process and representing actions performed in the plurality of unit operations manufacturing process and/or information collected for the plurality of unit operations in the particular manufacturing process (e.g., information collected before, during, and/or after one or more of the plurality of unit operations is/are performed); and (b) cause rendering of a graph-based visualization of the particular manufacturing process via the manufacturing management GUI, wherein the graph-based visualization comprises a plurality of interactive nodes [e.g., graphical icons, such as (e.g., color-coded) inter-connected circular icons], each interactive node of the plurality of interactive nodes representing an individual datapoint corresponding to a particular action that is performed in one of the plurality of unit operations and/or a particular set of information that is collected for a particular one of the plurality the unit operation (e.g., information collected before, during, and/or after the particular unit operation).

[0073] In another aspect, the invention is directed to a system for facilitating experimental process design and data collection for manufacturing production processes via an interactive GUI, the system comprising: a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to: (a) receive and/or access manufacturing process data corresponding to a particular manufacturing process and representing actions (e.g., unit operations in the particular manufacturing process) performed and/or information collected during the particular manufacturing process; and (b) cause graphical rendering of one or more interactive panels representing the actions and/or information collected during the manufacturing processes, the one or more interactive sub-panels comprising one or more (e.g., up to all) of the following: (i) a real-time data display panel comprising graphical rendering of data obtained from and/or input to one or more connected devices used (e.g., to perform unit operations and/or collect measurements) during the particular manufacturing process; (ii) a process design display panel comprising a graphical rendering of one or more unit operations performed during the manufacturing processes (e.g., as linked tiles); (iii) a data input and calculations panel comprising a graphical rendering of a plurality of fields (e.g., textual input boxes) for input of raw data and corresponding calculations; and (iv) a material preparation and data calculations panel comprising a graphical rendering of a plurality of input fields and/or output calculations corresponding to material preparation inputs and calculations.

[0074] Features of embodiments described with respect to one aspect of the invention may be applied with respect to another aspect of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0075] The foregoing and other objects, aspects, features, and advantages of the present disclosure will become more apparent and better understood by referring to the following description taken in conjunction with the accompanying drawings, in which:

[0076] FIG. 1 is a block flow diagram showing a CMC database management system, according to an illustrative embodiment.

[0077] FIG. 2 is a diagram depicting three different backend infrastructure schemas for view-based data integration for a CMC portal, according to illustrative embodiments.

[0078] FIG. 3 is a block flow diagram depicting a federated server for CMC data harmonization, according to an illustrative embodiment.

[0079] FIG. 4A is a view of a first image of a display screen or portion thereof comprising an interactive graphical user interface (GUI), according to an embodiment; and [0080] FIG. 4B is view of a second image thereof.

[0081] FIG. 5A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to an embodiment; and

[0082] FIG. 5B is view of a second image thereof.

[0083] FIG. 6A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to an embodiment; and

[0084] FIG. 6B is view of a second image thereof.

[0085] FIG. 7A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to an embodiment; and

[0086] FIG. 7B is a view of a second image thereof.

[0087] FIG. 7C is another view of an image of a display screen or portion thereof comprising an interactive GUI, according to an embodiment.

[0088] FIG. 8A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to an embodiment;

[0089] FIG. 8B is a view of a second image thereof; and

[0090] FIG. 8C is a view of a third image thereof.

[0091] FIG. 9 is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to an embodiment.

[0092] FIG. 10A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to an embodiment;

[0093] FIG. 10B is a view of a second image thereof; and

[0094] FIG. 10C is a view of a third image thereof.

[0095] FIG. 11 is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to an embodiment.

[0096] FIG. 12 is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to an embodiment. [0097] FIG. 13 A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to an embodiment;

[0098] FIG. 13B is a view of a second image thereof;

[0099] FIG. 13C is a view of a third image thereof; and

[0100] FIG. 13D is a view of a fourth image thereof.

[0101] FIG. 14A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment;

[0102] FIG. 14B is a view of a second image thereof; and

[0103] FIG. 14C is a view of a third image thereof.

[0104] FIG. 15A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment;

[0105] FIG. 15B is a view of a second image thereof;

[0106] FIG. 15C is a view of a third image thereof;

[0107] FIG. 15D is a view of a fourth image thereof;

[0108] FIG. 15E is a view of a fifth image thereof;

[0109] FIG. 15F is a view of a sixth image thereof; and

[0110] FIG. 16 is a view of a seventh image thereof.

[0111] FIG. 17 is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0112] FIG. 18 is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0113] FIG. 19 is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment;

[0114] FIG. 20A is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment. [0115] FIG. 20B is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0116] FIG. 20C is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0117] FIG. 21A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0118] FIG. 21B is a view of a second image thereof.

[0119] FIG. 21C is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0120] FIG. 21D is a view of a second image thereof.

[0121] FIG. 22A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0122] FIG. 22B is a view of a second image thereof.

[0123] FIG. 22C is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0124] FIG. 22D is a view of a second image thereof.

[0125] FIG. 22E is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0126] FIG. 22F is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0127] FIG. 23 A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0128] FIG. 23B is a view of a second image thereof.

[0129] FIG. 24A is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0130] FIG. 24B is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment. [0131] FIG. 24C is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0132] FIG. 24D is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0133] FIG. 24E is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0134] FIG. 24F is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0135] FIG. 24G is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0136] FIG. 24H is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0137] FIG. 24I is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0138] FIG. 24J is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0139] FIG. 25A is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0140] FIG. 25B is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0141] FIG. 25C is a view of a second image thereof.

[0142] FIG. 25D is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0143] FIG. 25E is a view of a second image thereof.

[0144] FIG. 26A is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0145] FIG. 26B is a view of a second image thereof. [0146] FIG. 26C is a view of a first image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0147] FIG. 26D is a view of a second image thereof.

[0148] FIG. 27A is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0149] FIG. 27B is a view of a second image thereof.

[0150] FIG. 27C is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0151] FIG. 27D is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0152] FIG. 27E is a view of a second image thereof.

[0153] FIG. 27F is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0154] FIG. 28A is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment

[0155] FIG. 28B is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment

[0156] FIG. 28C is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment

[0157] FIG. 28D is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment

[0158] FIG. 28E is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment

[0159] FIG. 28F is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment

[0160] FIG. 29A is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and [0161] FIG. 29B is a view of a second image thereof.

[0162] FIG. 29C is a view of an image of a display screen or portion thereof comprising an interactive GUI showing our new design, according to another embodiment.

[0163] FIG. 30 is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment;

[0164] FIG. 31 is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment;

[0165] FIG. 32 is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment

[0166] FIG. 33A is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment; and

[0167] FIG. 33B is a view of a second image thereof.

[0168] FIG. 34A is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0169] FIG. 34B is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0170] FIG. 34C is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0171] FIG. 34D is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0172] FIG. 34E is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0173] FIG. 34F is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0174] FIG. 34G is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment. [0175] FIG. 34H is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0176] FIG. 34I is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0177] FIG. 34J is a view of an image of a display screen or portion thereof comprising an interactive GUI, according to another embodiment.

[0178] FIG. 35 is a schematic illustrating steps and data sampling carried out across multiple manufacturing processes, according to an illustrative embodiment.

[0179] FIG. 36 is a block diagram illustrating various unit operations associated with multiple manufacturing processes, according to an illustrative embodiment.

[0180] FIG. 37 is a block-flow diagram of an example process for providing graph- based visualizations of manufacturing processes, according to an illustrative embodiment.

[0181] FIG. 38A is a screenshot of an example GUI showing a process graph representing a pharmaceutical product manufacturing process, according to an illustrative embodiment.

[0182] FIG. 38B is a screenshot of an example GUI showing a process graph representing a pharmaceutical product manufacturing process with an interactive pop-up corresponding to a node, according to an illustrative embodiment.

[0183] FIG. 38C is a screenshot of an example GUI showing a data health and selection matrix visualization, according to an illustrative embodiment.

[0184] FIG. 38D is a screenshot of an example GUI showing a data health and selection matrix visualization, according to an illustrative embodiment.

[0185] FIG. 38E is an annotated screenshot of an example GUI depicting relationships between process nodes and graphical display of datapoints, according to an illustrative embodiment.

[0186] FIG. 38F is an annotated screenshot of an example GUI depicting relationships between process nodes and graphical display of datapoints, according to an illustrative embodiment. [0187] FIG. 38G is a screenshot of an example interactive data analytics view, according to an illustrative embodiment.

[0188] FIG. 38H is a screenshot of two graphs generated via graph-based visualization tools described herein, according to an illustrative embodiment.

[0189] FIG. 38I is a screenshot showing multiple process graphs aligned and overlaid for comparison, according to an illustrative embodiment.

[0190] FIG. 39A is a block flow diagram illustrating a process for providing an experimental process design and data collection GUI, according to an illustrative embodiment.

[0191] FIG. 39B is a screenshot of an example experimental process design and data collection GUI, according to an illustrative embodiment.

[0192] FIG. 39C is a screenshot of an example experimental process design and data collection GUI, according to an illustrative embodiment.

[0193] FIG. 39D is a screenshot of an example experimental process design and data collection GUI, according to an illustrative embodiment.

[0194] FIG. 40 is a schematic showing an implementation of a network environment for use in providing systems, methods, and architectures as described herein, according to an illustrative embodiment.

[0195] FIG. 41 is a schematic showing exemplary computing devices that can be used to implement the techniques described herein, according to an illustrative embodiment.

[0196] The features and advantages of the present disclosure will become more apparent from the detailed description set forth below when taken in conjunction with the drawings, in which like reference characters identify corresponding elements throughout. In the drawings, like reference numbers generally indicate identical, functionally similar, and/or structurally similar elements. CERTAIN DEFINITIONS

[0197] About or Approximately: The term “about” or “approximately”, when used herein in reference to a value, refers to a value that is similar to the referenced value. In general, those skilled in the art, familiar with the context, will appreciate the relevant degree of variance encompassed by “about” or “approximately” in that context. For example, in some embodiments, the term “about” or “approximately” may encompass a range of values that are within 25%, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, or less of the referred value.

[0198] Manufacturing process: As used herein, the term “manufacturing process,” refers to any process involved in the design, pre-clinical testing, clinical testing, manufacturing scale-up, and commercial scale production run for producing a pharmaceutical product. For example, as used herein, a manufacturing process may include a laboratory experiment run to evaluate candidate pharmaceutical products, e.g., including synthesis of compounds and/or biologies as well as in-vitro assays and/or in-vivo tests, such as animal studies. In certain embodiments, a manufacturing process may refer to clinical tests or trials (e.g., in human subjects). In certain embodiments, manufacturing processes may include process design experiments used to scale up production, for example from small scale laboratory experiment or pilot level production to commercial scale production, or used to optimize manufacturing processes. In certain embodiments, a manufacturing process is a commercial scale process, used to produce pharmaceutical products for commercial use and/or sale. Pharmaceutical products may include small molecules, biologies, cell-therapies, and the like, and may comprise one or more active agents formulated together with compatible carriers (e.g., liquid or solid filler), solvents, diluents, or excipients.

Pharmaceutical products may take on a variety of forms, for example depending on desired administration approaches. For example, pharmaceutical products may be specially formulated for administration in solid or liquid form, including those adapted for the following: oral administration, for example, drenches (aqueous or non-aqueous solutions or suspensions), tablets, e.g., those targeted for buccal, sublingual, and systemic absorption, boluses, powders, granules, pastes for application to the tongue; parenteral administration, for example, by subcutaneous, intramuscular, intravenous or epidural injection as, for example, a sterile solution or suspension, or sustained-release formulation; topical application, for example, as a cream, ointment, or a controlled-release patch or spray applied to the skin, lungs, or oral cavity; intravaginally or intrarectally, for example, as a pessary, cream, or foam; sublingually; ocularly; transdermally; or nasally, pulmonary, and to other mucosal surfaces.

[0199] Unit operations: As used herein, unit operations refer to discrete steps or actions carried out in manufacturing processes. Unit operations may include operations involved in producing a pharmaceutical product or one or more ingredients thereof, as well as, for example, assays and experimental tests used to evaluate properties of compositions that are produced. For example, unit operations may include steps of obtaining various starting materials, material preparation steps, steps such as thawing, selection, wash or volume reduction steps, expansion steps, fill steps, formulation steps, freezing steps, transduction steps, harvesting, activation, various chemical synthesis steps, as well as analysis assays, such as various in-vitro assays (e.g., fluorescence-based assays, such as ELISA assays, flow-cytometry, cell viability assays, cytotoxicity assays, etc.) and sub-steps thereof, and/or in-vivo tests, such as animal model studies, and the like.

DETAILED DESCRIPTION

[0200] It is contemplated that systems, architectures, devices, methods, and processes of the claimed invention encompass variations and adaptations developed using information from the embodiments described herein. Adaptation and/or modification of the systems, architectures, devices, methods, and processes described herein may be performed, as contemplated by this description.

[0201] Throughout the description, where articles, devices, systems, and architectures are described as having, including, or comprising specific components, or where processes and methods are described as having, including, or comprising specific steps, it is contemplated that, additionally, there are articles, devices, systems, and architectures of the present invention that consist essentially of, or consist of, the recited components, and that there are processes and methods according to the present invention that consist essentially of, or consist of, the recited processing steps. [0202] It should be understood that the order of steps or order for performing certain action is immaterial so long as the invention remains operable. Moreover, two or more steps or actions may be conducted simultaneously.

[0203] The mention herein of any publication, for example, in the Background section, is not an admission that the publication serves as prior art with respect to any of the claims presented herein. The Background section is presented for purposes of clarity and is not meant as a description of prior art with respect to any claim.

[0204] Documents are incorporated herein by reference as noted. Where there is any discrepancy in the meaning of a particular term, the meaning provided in the Definition section above is controlling.

[0205] Headers are provided for the convenience of the reader - the presence and/or placement of a header is not intended to limit the scope of the subject matter described herein.

A. CMC Database Management Systems

[0206] FIG. l is a block flow diagram showing a CMC database management system for manufacturing a pharmaceutical, according to an illustrative embodiment. The system includes a process control module, a process design and execution module, a process modeling module, a digital monitoring room and business insight module, and a knowledge base module. The process control module includes control software that allows for real-time decisions and predictions/insights for manufacturing processes (lab, pilot, or commercial scale). Data passes between the process control module and the knowledge base (in both directions).

[0207] The process design and execution module of FIG. 1 includes a process designer, a process director, and a data collection submodule. The data collection module includes functionality that provides for custom module development and development of ontology-guided web components. The process designer allows for interactive, drag-and- drop, GUI-widget enabled combination of unit operations and variable setting for design of manufacturing processes. Data passes between the process design and execution module and the knowledge base (in both directions). As described in further detail herein, in certain embodiments, among other things, the process designer presents a user with an intuitive graphical approach for designing manufacturing processes, which may be represented and stored as graphs, e.g., in the knowledge base. In this manner, users may create complex and detailed process graph data structures via an intuitive graphical programming interface, without coding expertise.

[0208] The process modeling module provides data ready for hybrid, statistical, and optimization modeling of a pharmaceutical product manufacturing process, and includes data preparation, model creation, and model validation submodules. The process modeling module, can be integrated to allow for connection with, for example, a machine learning (ML) module that implements one or more specific machine learning algorithms, such as an artificial neural network (ANN), random forest, decision trees, support vector machines, and the like, in order to determine, for a given input, one or more output values. The ML algorithms may be trained as new data is gathered and/or may be locked at one or more specific times. Data passes between the process modeling module and the knowledge base (in both directions).

[0209] The digital monitoring room and business insights module includes a data monitoring dashboard (e.g., a proprietary CMC development portal), a real time analysis submodule, an insights module, and an enterprise module. The data monitoring dashboard may include, for example, a “stories” -based visual layout/presentation of text in combination with real-time updated structured (tagged) data with user-interactive features, as shown in more detail herein. The insights module may include, e.g., analytical tools for producing product and/or manufacturing process insights, including interactive features such as tiling with expanding graphs, a process dashboard, and a patient dashboard layout as shown in more detail herein. Data generally passes from the knowledge base to the digital monitoring room and insights module.

[0210] The knowledge base module provides scalable computation and storage of data gathered from and transmitted to the various other modules. Among other things it provides taxonomy, structure, and hierarchy to handle data granularity, ontology, and data harmonization. Process definitions provide tags, for example, for collected data according to the device, materials, and processes used. In certain embodiments, provided taxonomies include classification and/or categorization of data, thereby providing a structured approach. In certain embodiments, provided systems utilizes hierarchy, aiding in managing data at different levels of detail (data granularity). In certain embodiments, provided systems and methods include ontologies (e.g., stored ontologies), , which represent nature and interrelations of data. This helps in harmonizing or standardizing data from different sources for consistency and compatibility. Furthermore, the process definitions in this system include tags. These tags are applied to data based on specific criteria such as a device used for data collection, materials involved, and processes employed. This tagging facilitates easier identification, sorting, and use of data.

[0211] In certain embodiments, the system may utilize a view-based data integration system (VDIS) to produce responses to user queries, where the VDIS accesses multiple data sources with heterogeneous data formats via a federated server, resolves one or more inconsistencies from the combined data, and produces integrated results in response to the user query. In the context of using ontology for harmonizing multiple data sources for federated queries with GraphQL endpoints, provided processes may include one or more of the following:

[0212] Ontology-Based Harmonization: In certain embodiments, ontologies provide a structured framework to define and represent knowledge. In the context of multiple data sources, ontologies are used to harmonize and/or unify data. This means different data sources, even if they use different terminologies or structures, are brought into a common understanding or format. This harmonization capability facilitates integrating data from diverse sources, as it ensures that similar concepts from different databases are recognized as such (e.g., as related).

[0213] Multiple Data Sources: In certain embodiments, systems and methods of the present disclosure include multiple data sources - various databases or information repositories where data is stored. These sources may have different structures, formats, or models for representing data.

[0214] Federated Query: In a federated system, queries may be made across multiple autonomous databases. Among other things, the system allows a user to make a single query that accesses several databases, without needing to interact with each database individually. This is particularly useful in environments where data is not centralized.

[0215] GraphQL Endpoints: GraphQL is a query language for APIs and a runtime for executing those queries by using a type system, e.g., that a user, particular group of users, company, etc., defines for their data. In this context, GraphQL endpoints are the interfaces through which queries are made to the federated system. They allow users to request exactly what they need and nothing more, making it efficient and precise. GraphQL also enables complex queries that involve multiple types of data, which is essential in a federated system where data is coming from various sources.

[0216] In certain implementations, these systems use ontology to standardize and harmonize data from multiple sources, allowing for efficient and effective data integration. Through federated queries, users can access this integrated data using GraphQL endpoints, which offer a flexible and powerful way to retrieve exactly what they need from the combined data sources.

[0217] In certain embodiments, the data sources accessed by the database management system are at least partially harmonized at the point of data collection by restriction of data entry to a plurality of predetermined fields and/or values. In this way, data collected from an instrument at different times, for example, by different operators, benefit from uniform labeling of the process input variables provided by the operators. As a result, less unresolvable data is produced. In certain embodiments, provided systems utilize ontology for standardization. Ontology, refers to a particular set of rules and structures that define how data is to be organized and interpreted. In certain embodiments, it provides a common framework or language for describing and categorizing data. Ontology approaches can be accomplished by creating and defining ontologies stored in the knowledge databases. For example, users, groups of users, organizations, etc. may pre-define materials, devices, step names/types, and also specific types of data/variables (e.g., DMSO Exposure Start time) into the knowledgebases and create the links between the meta-data (e.g., particular components and their manufacturers (e.g., a PL07-2G bag is manufactured by OriGen Biomedial)). Accordingly, in certain embodiments, as a particular user (e.g., operator) is designing an experiment, information from the knowledge bases feed into the process design such that operators may be restricted to using only the pre-registered materials, device, etc. In this manner, provided systems and methods can, in certain embodiments, enforce a common ontology around unit operations, materials, and their related date. For example, rather than allowing a user to type in, without restriction, names for e.g., components or materials used (e.g., a particular bag type), they may be restricted to predefined fields (e.g., an operator can only select and use a "PL07-2G" bag), thereby preventing individual and/or multipe users from inputting different data to represent a same parameter, material, component, etc., in an inconsistent fashion (e.g., without this feature the operator might write in PL7, or PL-7, or PL07 bag which the operator understands as the same thing, but would all be understood by the computer as different materials or require a great deal of coding to establish as similar). In the same way, the operator could say indicate the manufacturer as OriGen or OriGen Bio or OriGen Biomedical which would cause the same issues.

[0218] In certain embodiments, systems and methods include a harmonization at data collection point: whereby the process of harmonization begins as soon as data is collected. In certain embodiments, this is achieved by utilizing approaches for restricting data entry to a pre-defined set of fields and/or values as described herein. In this manner, the data collected is immediately structured and standardized according to the ontology, reducing variability and inconsistency. CMC manufacturing systems and methods of the present disclosure may offer predetermined fields and/or values, specific categories or parameters set out by the ontology. By limiting data entry to pre-defined fields and values, approaches described herein can ensure that the data collected is uniform and conforms to a standardized format. Among other things, this facilitates later stages of data processing and analysis, as it simplifies and streamlines these processes.

[0219] Uniform Labeling by Different Operators: In a practical scenario, different operators might use the instrument at different times. The use of a standardized ontology ensures that, regardless of who operates the device or when it is used, the data collected will be consistent. This is because all operators are required to input data in the same way, using the same predetermined fields and values. [0220] FIG. 2 is a diagram depicting three different backend infrastructure schema for view-based data integration for a CMC portal, according to illustrative embodiments. These schemas are used, for example, to build a single source of truth for queried data, e.g., to resolve inconsistencies among data retrieved from multiple data sources. In one embodiment, the view-based data integration system (VDIS) comprises a both-as-view (BAV) backend infrastructure, shown in the middle. This is also known as a global and local as view (GLAV) backend infrastructure. In the BAV (aka GLAV) infrastructure shown in FIG. B, for example, Global Schema and Local Schema are connected via transformation pathways in both directions (Global to Local and Local to Global), where RDB means Relational Database, RDF means Resource Description Framework, and XML means Extensible Markup Language. In another embodiment, the VDIS comprises a global-as-view backend infrastructure, shown at left in FIG. 2. Here, the Global Schema is connected to Local Schema via View Definition (from Global to Local). In another embodiment, the VDIS comprises a local-as-view backend infrastructure, shown at right in FIG. 2. Here, the Local Schema is connected to Global Schema via View Definition (from Local to Global). In any of these examples, the VDIS may include a mediator that converts a query into a plurality of source-specific queries and sends the source-specific queries to one or more wrappers for execution. The backend infrastructure queries multiple sources comprising heterogeneous structured data that are integrated into a unified view. In certain embodiments, the system implements a graph-based real-time digitalization and contextualization engine. In certain embodiments, one or more of the multiple data sources are harmonized at the point of data collection by restricting data entry to a plurality of predetermined fields and/or values.

[0221] FIG. 3 is a block flow diagram depicting a federated server for CMC data harmonization, according to an illustrative embodiment. In this illustration, the data management system includes a federated server which receives both ontology-guided manufacturing data as well as ontology-guided clinical data (e.g., data harmonization guided by ontologies, e.g., as described herein). In certain embodiments, only manufacturing data is used, while in other embodiments, only clinical data is used. The federated server may include the database management system (e.g., a VDIS) that receives a query and produces a query response with integrated, harmonized data. In certain embodiments, the system includes an ontology harmonization process as depicted. B. Graphical User Interfaces

[0222] Presented herein are graphical user interfaces for use with the database management systems described herein, and/or isolated modules thereof.

[0223] Described herein are embodiments of an interactive graphical user interface (GUI) that, among other things, visually conveys to a user information relating to (i) the creation and/or modification and/or analysis of unit operations in manufacturing processes, such as cell and gene therapy manufacturing processes, and data generated therefrom, (ii) a combination of live data from a database and textual information, and (iii) interactive analysis of data, for example, a patient data visualization system, and systems for analysis of data pertaining to manufacturing processes. For example, in certain embodiments, GUI of the present disclosure provide a user with multiple levels of detail regarding experimental and manufacturing processes, which may be visually presented to a user in various formats including particular combinations of charts and/or dynamic elements that a user may navigate in an interactive fashion. i. Process Director

[0224] For example, FIGs. 4A - 12 show views of a GUI comprising one or more linked tiles. In certain embodiments, each tile represents a step in a particular experimental and/or manufacturing process. GUI views, such as those shown in FIGs. 4A-12 may, accordingly, visually convey to a user various steps in a particular process and interrelations (e.g., input and/or output relationships) between steps. In certain embodiments, for example as shown in FIGs. 4A and B, one or more tiles are dynamic, such that upon a user interaction with a particular tile (e.g., via a mouse click or hover, e.g., via a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, which may convey to a user additional information pertaining to the process step represented by the particular tile. For example, FIG. 4A shows a first image of a GUI view, displaying a plurality of linked tiles, and FIG. 4B shows a second image of the GUI view in which, following a user interacting with a particular tile, a pop-up window has appeared associated with that particular tile. Additional embodiments are shown in FIGs. 5A-6B. [0225] In certain embodiments, for example as shown in FIGs. 7A and 7B, a pop-up window may display expandable sub-displays. In certain embodiments, for example as shown in FIGs. 8A-8C and FIGs. 10A-C pop-up windows are scrollable, such that a user may scroll through vertically arranged information pertaining to a particular step - e.g., transitioning between the series of three images shown in FIGs. 8A-C, e.g., transitioning between the series of three images shown in FIGs. 10A-C.

[0226] FIGs. 7C, 9, 11, and 12 show various embodiments of tile displays that may be used, additionally or alternatively.

[0227] Process diagrams generated in accordance with CMC manufacturing technologies described herein can provide a convenient and informative way to represent sequences and/or connections between different stages of an experiment and/or production process. In certain embodiments, each linked tile corresponds to a node which represents a particular unit operation in a particular manufacturing process. Lines linking one tile to another convey flow of materials and/or data from one unit operation to another. Conveying connections between various unit operations in this manner can provide a great deal of context and information about how nodes (unit-operations) are related to each other and, in certain embodiments, can be used to dictate flow and/or use of data, for example for automation of processes, portions thereof, associated data management tasks, and the like. In certain embodiments, relations between nodes can be used in modeling techniques, for example as input features to neural network models.

[0228] For example, links between tiles, shown as lines in FIGs 4A-12, lines may provide context regarding, process actions, such as when cells were split into one or more groups of cells (e.g., splitting of cells into a transduced therapeutic arm and a process control arm) and/or when groups of cells are combined (e.g., addition of particular activating cells). Allowing for users to create and/or visualize connections between unit operations in this manner improves the capabilities of process views as described herein to present detailed information over other approaches, for example, accordion and list style displays of nodes in which this connection context information would be lost and/or obscured. ii. Process Designer

[0229] In certain embodiments, GUI views of the present disclosure visually convey to a user information associated with various steps in a process in a manner that allows the user to design new processes. For example, FIGs. 13 A-D show GUI views comprising a tile representing a particular process step together with an associated pop-up window that displays one or more editable fields for parameters that a user may select and/or edit. In this manner, GUI views such as those shown in FIGs. 13 A-D facilitate user creation and design of new processes, e.g., via a graphical editor, by visually conveying information associated with new process steps in an intuitive and accessible manner. FIGs. 14A-C show another series of images of a GUI view for user design of new processes, used in certain embodiments. FIGs. 15A-F and 16 show another series of images of a GUI view for user design and/or analysis (e.g., as shown in FIG. 16) of new processes, used in certain embodiments. FIGs. 17-19 show images showing various tile designs and layouts, used in certain embodiments.

[0230] In certain embodiments, as a user creates process diagrams as shown, e.g., in FIGs. 13A-19, as they create tiles, input data and information, draw connection lines, and otherwise interact with a GUI, underlying graph data structures - e.g., nodes and links between them (e.g., edges) which represent manufacturing process unit operations and material and data flow, are created, allowing users to generate complex data structures in a graphical programming / “no-code” fashion. Graph data structures created in this manner can, e.g., subsequently, be provided (e.g., as input) to various other modules, e.g., for comparison between other processes (e.g., as described in Section C, below, with respect to FIGs. 38A-F), generation of data analytics and interactive views (e.g., any of the analytics views shown in FIGs. 20A-28F and/or described in Section B.iii, as well as, additionally or alternatively, shown and described in Section C below and FIGs. 38A-F, below), performing process control and/or optimization tasks (e.g., in connection with any of the views described in sections B.iv-B.vi and D, and shown in FIGs. 29A-31J and 39A_ D), and modeling (e.g., via machine learning techniques). iii. Data Displays and Interactive Views

[0231] In certain embodiments, GUI views of the present disclosure visually display data associated with and/or generated by various experimental and/or manufacturing processes.

Patient Tiles

[0232] Data display views of the present disclosure may include, for example, views for visually presenting clinical trial data to a user, for example as shown in FIGs. 20A-23D. For example, in certain embodiments, clinical trial data display views of the present disclosure may include charts comprising patient tiles, each representing a particular patient participating in a clinical trial. As shown in FIGs. 20A-C, various embodiments of patient tile charts may include tiles of varying color, shading, line-styles, etc., for example to visually convey data such as clinical responses of patients. In certain embodiments, patient tile/summary charts may be displayed in association with text, for example as part of an interactive report or story. In certain embodiments, patient tile charts may be provided as part of an interactive dashboard, whereby a user may click or otherwise select a particular patient tile to view additional detail pertaining to the particular patient, for example via a pop- up as shown in the series of images in FIGs. 21A and B, FIGs. 21C and D, and FIGs. 23 A and B. In certain embodiments, patient tile views of the present disclosure include views that display patient tiles that include graphs showing variation (e.g., with time) of various biomarkers, for example as shown in FIGs. 22A-F. Biomarker graphs may be displayed, for example, as line as shown in FIGs. 22A-D, in a shaded fashion, for example, as shown in FIGs. 22E and F, or in other manners.

Cell Data Views

[0233] In certain embodiments, data display views of the present disclosure include cell data views that track variation in various metrics (e.g., performance metrics) for multiple cell lines over a course of manufacturing and/or experimental processes. Cell data views may be presented as organized dashboards as shown in FIGs. 24A-J. In certain embodiments, interactive dashboards for viewing cell data display data for one or more lots. In certain embodiments, e.g., as shown in FIGs. 24A-C, data for multiple lots may be displayed and visually presented to a user. In certain embodiments, for example as shown in FIG. 24D, a particular lot may be viewed by itself.

Swimmer’s Chart Views

[0234] In certain embodiments, data display views of the present disclosure include views that present a user with a visual dashboard including a swimmer’s chart that visually convey patient response to treatment over time, for example as shown in FIGs. 25A-C. In certain embodiments, for example as shown in FIGs. 25B and C, swimmer’s chart views according to the present disclosure may include interactive and animated elements whereby a user may select data points on within charts to cause display of additional information. For example, in certain embodiments, a user selection of a data point on a chart may cause a popup effect, such that FIGs. 25B and C appear in sequence.

Release Metrics and Characterization Views

[0235] In certain embodiments, data display views of the present disclosure provide for visual display of release metrics and characterization of one or more drugs. In certain embodiments, product release data may be displayed in charts in connection with text, for example as an interactive and/or dynamic report or story, e.g., as shown in FIGs. 26A and B, and FIGs. 26C and D. In certain embodiments, release metric views may be presented as a visual dashboard (e.g., an interactive dashboard), for example as shown in FIGs. 27A-F

Starplots

[0236] In certain embodiments, process and/or experimental data may be displayed in a circular fashion, for example to indicate a circular nature of process / product development, as shown in FIGs. 28A-E.

Process Data Views

[0237] In certain embodiments, data associated with various processing steps may be displayed in interactive stories and/or charts, for example as shown in FIG. 28F. iv. Process Control and Monitoring Views

[0238] In certain embodiments, GUI views of the present disclosure include graphical displays that visually convey to a user progress and/or performance of various manufacturing and/or experimental processes, for example as shown in FIGs. 29A-31. In certain embodiments, process monitoring views include interactive features, whereby additional visual elements appear in a dynamic fashion. For example, FIGs. 29A and B show a first and second images in a dynamic display, whereby a visual element appears to a user, for example upon a user selection of a particular step in a process via the view shown in the first image. v. Report Customization and IND Reporting

[0239] In certain embodiments, GUI views of the present disclosure include graphical displays used in connection with a user creation and/or customization of report generation. For example, FIG. 32 shows a visual dashboard that allows a user to customize or compose reporting features by visually displaying data elements and reporting features to a user to select. In certain embodiments, figures displaying data charts are formatted and display particular variables, data etc., according to user interactions and selections with composition dashboards such as those shown in FIG. 32. For example, charts shown in FIGs. 33A and B are examples of charts composed according to selections made by a user via interaction with a composition dashboard according to the embodiment shown in FIG. 32. In certain embodiments, designs as shown in FIGs. 33A and B include dynamic figures, whereby visual elements appear in dynamic fashion upon a user interaction with one or more data points. vi. Device Toolkit

[0240] In certain embodiments, GUI views of the present disclosure visually display listing and information pertaining to various devices that may be used in experimental and/or manufacturing processes. FIGs. 34A-J show various embodiments of device display and comparison views. C. Graph-Based Visualization for Pharmaceutical Product Manufacturing Process Data Harmonization, and Generation of Interactive Data Views

[0241] In certain embodiments, CMC management technologies of the present disclosure provide graph-based visualization tools that allow users to analyze data associated with one or more experimental and/or manufacturing processes used for production of pharmaceutical products and/or variations thereof. In particular, graph-based visualization and data analysis tools described herein can be used to automatically and/or semi- automatically (e.g., in connection with user review and/or input) generate visualizations facilitating experimental and/or manufacturing process inspection and to harmonize data generated across multiple processes and/or process runs.

[0242] For example, among other things, interactive graph-based CMC management tools may include one or more of the following elements, which may be provided (e.g., rendered) individually or together via one or more GUIs or windows, sub-windows, panels, etc., thereof:

[0243] Process Graph. In certain embodiments, graph-based visualization tools of the present disclosure include generation and/or rendering of process graphs that represent experimental and/or manufacturing processes for production of pharmaceutical products, including biologies, such as cell-based therapies and biologic drugs. Process graphs may include multiple nodes, each representing a datapoint corresponding to a unit operation in a particular experimental and/or manufacturing process where information is collected and/or an action is performed. Various approaches for capturing and/or representing these datapoints, as well as how users interact with them, are described in further detail herein.

[0244] Data Health and Selection Tools. In certain embodiments, graph-based visualization tools of the present disclosure include data health and selection tools with capability to assess health or integrity of data collected at various steps in an experimental and/or manufacturing process. As described in further detail herein, data health and selection tools may use one or more criteria used to evaluate data health, such as completeness, accuracy, consistency, and the like. Additionally or alternatively, users may interact with data as conveyed by process graphs to select a set of datapoints for more focused analysis, for example thereby influencing (e.g., updating, modifying) process graph visualizations and/or causing generation of additional GUIs, such as various data display and interactive views described herein (e.g., in section B, above).

[0245] Comparison and Alignment of Multiple Processes. In certain embodiments, graph-based visualization tools of the present disclosure provide for comparison and/or alignment data from multiple experimental and/or manufacturing processes, for example in an automated and/or semi-automated (e.g., in connection with user interactions, such as review and selection actions) fashion. Among other things, approaches described herein may (e.g., automatically) overlay multiple process graphs, compare them structurally, and align them based on datapoints. For example, process comparison and alignment tools may (e.g., automatically) identify and handle discrepancies, missing data, or anomalies and may be used to generate harmonized datasets for further analysis, such as mathematical modeling.

[0246] Accordingly, among other things, graph-based visualization tools of the present disclosure address challenges presented by misaligned data across multiple experimental and/or manufacturing processes and/or within a single process that may be executed under varying conditions. Achieving automated harmonization of such data is a significant challenge, which, if not addressed, impedes efficient and accurate analysis, which can, in-tum, dramatically influence a user and/or organizations ability to optimize and/or maintain quality of manufacturing processes, and/or develop new ones. Among other things, systems and methods of the present disclosure address the challenge of analyzing data from experiments with varying sampling plans. As described in further detail herein, CMC manufacturing technologies (e.g., graph-based visualizations) aid in aligning sampling points to maximize overlap for effective comparison and/or, in certain embodiments, identifies overlapping points in existing data for efficient real-time analysis.

[0247] For example, FIG. 35 is a schematic depicting a process flow diagram for a manufacturing procedure, showcasing different stages labeled by days, such as Day 0, Day 6, Day 9, Day 14, and Day 24. As shown in the figure, each stage includes various operations (e.g., thaw, wash, NK selection, transduction, etc.).

[0248] Dashed lines in the figure separate days and indicate temporal progression of depicted processes, while vertical arrows highlight specific data sampling points (labeled “Sampling AD”). . As evident from the figure, data sampling is carried out at different times for different processes - for example, this misalignment between processes can be seen by the non-uniform placement of sampling points across the different stages or process flows. In an ideal, aligned, set of processes, these sampling points would occur at corresponding stages across each distinct process flow.

[0249] In certain cases, researchers may use diagrams such as the one shown in FIG. 366 in process engineering to map out and compare different process flows. In the context of a manufacturing process, these differences could represent experimental variants or optimizations tailored to specific goals. For example, the schematic shown in FIG. 36 illustrates a complex set of processes, each with multiple steps. Each block in the figure represents a process step, and these are labeled with identifiers.

[0250] A researcher or engineer analyzing a schematic such as the one shown in FIG. 36B may, for example, aim to accomplish any of: (i) identify which steps are critical control points where conditions must be strictly managed, (ii) understand flow of materials and/or information through a system, (iii) compare the efficiency or yield of different processes, and/or (iv) ensure compliance with regulatory standards by maintaining consistent process conditions. Static versions of schematics such as the one shown in FIG. 36B, created, e.g., via previous techniques that may, among other things, fail to convey information about actual data collection and require careful review and rely on the user to manually identify and analyze differences between processes, and their impact on performance and results. In contrast, CMC manufacturing platforms of the present disclosure merges the ability to collect and link actual data collection with the diagram. Moreover, while not all the data may be directly visible at this level, by providing dynamic nodes that are clickable/expandable and customized for each node type techniques of the present disclosure allow users to inspect and analyze data collected and/or input data at the same time. In this manner, systems and methods described herein facilitate automated identification and analysis of differences between processes.

[0251] In certain embodiments, structural differences between different processes are indicative of variations in conditions (e.g., temperature, duration, chemical concentration) and a sequence and/or presence of certain steps. Although the unit operations — basic steps or phases in a process — may be generally similar to other processes, specific conditions and/or sequences can greatly affect the outcome or the nature of the product or result. Visual representation tools can, accordingly, be extremely valuable process optimization, troubleshooting, and ensuring that the processes meet desired specifications. For example, changing a device that performs the unit-operation and/or a particular parameter value (e.g., spin speed, total volume, duration, etc.) within a unit-operation can have a significant impact on the quality, recovery, efficiency, etc. of the output of that unit-operation, which could in turn, impact features such as biology/efficacy of the product, as well as, additionally or alternatively, factors like a cost of manufacturing, number of doses produced per manufacturing run, and the like. Accordingly, despite overall similarities between diagrams such as those shown in FIG. 36B, inputs into the diagrams from the operator while performing a study can have significant impact. Accordingly, among other things, CMC systems and methods described herein and their use of common ontologies greatly facilitate automating and identifying commonalities and/or differences between studies, as well as performing analyses, e.g., to determine if device or parameter changes have important impact.

[0252] Among other things, as described herein, graph-based visualization tools of the present disclosure provide users with technologies for visually representing one or more manufacturing processes via a graph-based approach that readily conveys and automatically highlights differences in conditions and unit operations and their exact nature. Graph-based tools described herein provide information pertaining to data collection and may be used to automatically highlight misaligned data points. This approach facilitates the identification and rectification of data alignment issues, thereby streamlining data analysis for research and process development performed in creation and production of pharmaceutical products such as cell-based therapies and biologic drugs. i. Process Graphs with Interactive Nodes

[0253] Turning to FIG. 37, in certain embodiments, a graph-based visualization tool 3700 may access manufacturing process data from a database 3702 and use it to generate and/or render a graph-based visualization 3704 comprising a process graph 3712 representing a manufacturing process or processes.

[0254] A screenshot of an example graph-based visualization is shown in FIG. 38A. As shown in the figure, a manufacturing process may be represented and displayed via process graph. Each node in the process graph represents a datapoint corresponding to a unit operation in the particular manufacturing process that it (i.e., the process graph) represents. A node may comprise information regarding current data status and content (e.g., in real- time) at the datapoint it represents. Within a graph-based visualization, nodes may be dynamic, such that, for example, a user interaction (e.g., a mouse hover, click, tap or long press on a touch screen, etc.) with a particular node causes display of a tooltip showing current data status at the represented datapoint, including data collected at various stages of the manufacturing process. A process graph outlines a complex manufacturing experiment of manufacturing procedure over a series of days and may be rendered and used for experimental design and process execution to visualize and track the different stages of an experiment in real-time.

[0255] As generated and/or rendered via graph-based visualization technologies of the present disclosure, may include all or various subsets (e.g., combinations) of the following features:

[0256] Experiment Outline. In certain embodiments, graphs are displayed as an experiment outline, providing a high-level outline of an experiment including process steps and (e.g., approximate) order in which they were performed, days particular process steps were performed, how the process steps are related to each other (e.g., upper half of FIG. 38A) and an overview of the various conditions/arms evaluated during the experiment and how those conditions are related to each other (e.g., lower half of FIG. 38A).

[0257] Timeline. In certain embodiments, process graphs may include a timeline, representing a plurality of timepoints, such as days, over which a particular experiment or manufacturing process represented by the graph is performed. As shown in FIG. 38A, a timeline may be represented along a horizontal axis, with labeled circular icons used to visually represent individual timepoints - days running from Day -1 to Day 21. Other fashions of visually representing a timeline, for example along a vertical axis and/or using other forms of icons, other units (e.g., hours, weeks, etc.) may be used.

[0258] Process Unit operations. In certain embodiments, process graphs may visually identify individual process unit operations that are carried out during a manufacturing process. Individual process unit operations may be represented, for example, via combinations of textual labels and icons or markings that convey particular unit operations performed as well as, optionally, times at which they are carried out and/or their relation (e.g., temporal) with respect to other unit operations. For example, the graph-based visualization shown in FIG. 38A includes a series of textual labels along a top row [of nodes], identifying various unit operations such as "Material Preparation," "Activation," "Transduction," and "Formulation,” etc. In FIG. 38A, textual labels also include a numerical component, identifying a particular day on which each unit operation is performed, and the textual labels are arranged in sequence, from left to right along a horizontal axis, to mark a sequence of operations performed over time. Dotted vertical lines running down from each textual label provide a visual guide for planned schedule for each unit operation and/or a temporal mapping of the manufacturing process.

[0259] Data Points (Nodes). As shown in FIG. 38A, datapoints in a manufacturing process where information - measurements and/or recorded observations - associated with and pertinent to a particular unit operation is collected are represented via nodes. Nodes may be rendered as icons, such as filled circles as shown in FIG. 38A. In the figure, each circle is a node and is located so as to be visually aligned with a particular unit operation - i.e., in the figure, placed on a dotted vertical line running down from a textual label identifying a particular unit operation - thereby identifying a datapoint associated with that particular unit operation.

[0260] Dynamic Nodes and Tooltips. In certain embodiments, nodes are rendered in a dynamic fashion, such that, for example, a user interaction with a particular node, for example via hovering over and/or selecting a node, reveals a tooltip with the current data status at that point, such as quantitative data or qualitative observations. FIG. 38B shows an example pop-up rendered following a user interaction with a particular node. [0261] Connectivity. In certain embodiments, process graphs may represent dependencies or sequences of material and/or data flow from one unit operation to another via rendered connections between various nodes. For example, as shown in FIG. 38A, node connectivity may be rendered as lines connecting nodes across a timeline.

[0262] Data Collection Points. Specific points where data is collected are marked along the process. Important checkpoints for quality control or measurements necessary for process evaluation.

[0263] Arms. In certain embodiments, process graphs of the present disclosure may include and/or represent one or more (e.g., distinct) arms, each representing a different experimental condition and/or variations of a baseline process. In FIG. 38A, arms are rendered as various smaller graphs positioned beneath the timeline. Each line in the arms section indicates a different arm/condition as defined by the operator. Labels are provided to help clarify the focus of those steps and/or to distinguish and identify the nodes as belong to one condition so that the corresponding data collected from the lab is placed into the correct node and we are not mixing data across conditions. In this case, the base process might be steps following the standard or control process while the others are steps that make experimental changes to the process and or are supplementary to the base process — e.g., making media, preparing materials, etc.

[0264] Baselines Process and Base Process Graphs. Baseline processes may be controls and/or standard procedure, and may be rendered as a base process graph. Textual labels, color schemes, icon styles, positioning, and the like, may be used to visually identify a baseline process as such in a graph-based visualization. For example, in FIG. 38A, a baseline process is identified and displayed as a line of nodes directly below the timeline. In the process graph of FIG. 38A, the baseline process is likely a standard process against which other variations are compared.

[0265] Variations and Outputs/Endpoints. In certain embodiments, graph-based visualizations may include one or more auxiliary sub-graphs, each corresponding to and representing a variation to experimental conditions and/or the baseline version of the manufacturing process. For example, FIG. 38A shows auxiliar sub-graphs representing variations labeled as "Ver 1.1," "Ver 1.2," "Ver 2.1," "Ver 2.3," etc., and different dosages of "Condition 1," “Condition 2,” “Condition 3,” which represent different experimental arms or conditions. In this manner, graph-based visualization tools may be used to convey variations in materials used, process conditions, or specific unit operations taken. Additionally or alternatively, different process endpoints and/or outputs may also be represented (e.g., by endpoint graphs). For example, as shown in FIG. 38A, sets of nodes labeled “Out. 1,” and “Out. 2,” represent different endpoints and/or outputs of the process, such as different ways of processing or storing a final product. As described herein, in the example sub-graphs shown in FIG. 38A, lines refer to an experimental condition or interrelated subsets of the process such as preparing a material (e.g., culture media) that then feed into the process containing the cells. As noted above, the arms/condition sections are used to help orient the operator to the specific tasks being performed and to identify the various arms in a descriptive way so that data collected in the lab is inputted into the corresponding node and counts/volume, etc. are not mixed between conditions

[0266] Accordingly, process graphs of the present disclosure facilitate visualizing and managing complex manufacturing processes. Among other things, they allow researchers to track progress of experiments, compare different conditions or variations side-by-side, and ensure that data is collected systematically at designated points throughout processes. The ability to visualize the entire process in this manner helps in identifying bottlenecks, ensuring consistency, and facilitating data-driven decision-making. ii. Data Health and Selection for Display

[0267] In certain embodiments, graph-based visualization tools may include GUIs allowing a user to view collected datapoints, assess their health, and select points to generate charts (e.g., interactive charts) that facilitate focused analysis of various facets of bioproduction processes.

[0268] For example, in certain embodiments, graph-based visualizations may be generated and/or rendered 3704 to include a data health and integrity display 3722 that facilitates visualization and assessment of data health. Data health and integrity displays may include and visually convey a plurality of datapoint indicators, each representing a collected and/or input value of the data parameter and/or variable at a particular time point and/or unit operation during the particular manufacturing process.

[0269] Example visualizations comprising rendered datapoints are shown in FIGs. 38C and 38D. Each of FIGs. 38C and 38D shows a streamlined process graph and, beneath, a data health and selection matrix. The data health and selection matrix is arranged into a plurality of rows and columns, with each vertical column corresponding to a particular day and/or unit operation in the streamlined process graph shown in the upper portion of the display, aligned with the timeline. Each horizontal row represents a different data parameter or variable being monitored or controlled throughout the process. Example data parameters and/or variables include, for example and without limitation, viable cell counts, volumes, concentrations, and other pertinent metrics.

[0270] In the example screenshots shown in FIGs. 38C and 38D, datapoint indicators may be rendered as dots to signify presence or absence of data at particular unit operations. Color coding may be employed, for example, to differentiate between collected data, missing data, and planned but skipped data collection points. For example, in FIGs. 38C and 38D black dots indicate collected data, blue dots identify selected data points for detailed analysis, and the absence of a dot indicates missing data. Visually conveying and differentiating between datapoints in this manner allows users to quickly assess completeness of data across a manufacturing process and/or identify areas of concern in the data collection process. Data health and selection matrix displays such as those shown in FIGs. 38C and 38D can highlight patterns in data availability or systematically missing data, thereby ensuring data integrity and robustness in manufacturing processes.

[0271] In certain embodiments, data health and integrity matrices such as those shown in FIGs. 38C and 38D are interactive, allowing users to select specific data points (as indicated by the color changes) to be used for generation of one or more additional graphs that can be displayed and interacted with via a data analytics GUI, which can be used for more detailed and/or targeted analysis of particular unit operations and/or parameters that are controlled and/or measured during a manufacturing process.

[0272] FIG. 38E and 38F illustrate correspondences between various nodes and/or datapoints and underlying values of measured parameters. By combining process graphs with a data health and selection matrix, graph-based visualization tools of the present disclosure provide users with a comprehensive overview of the process and its associated data. Among other things, they support decision-making, process optimization, and detailed analysis by making it possible to visualize an entire manufacturing process and its data landscape in one integrated view.

[0273] FIG. 38G shows a screenshot of an example data analytics interface, referred to as a “Cell Journey” chart, generated following user selection of one or more datapoints as described herein. The Cell Journey analysis interface shown in FIG. 38G provides visualizations representing a step-wise analysis of process metrics and can be used to provide insight into cell behavior, process efficiency, and/or quality control.

[0274] Data analytics interfaces of the present disclosure may include a header portion, comprising summary statistics and/or graphical representations of data corresponding to the selected datapoints collected over multiple lots - batches and/or experimental groups corresponding to the particular manufacturing process. For example, the screenshot in FIG. 38G includes a tally (“99 Lots”) of different production batches or experimental groups, a “Products” tab listing different product lines or experiments (e.g., A1, A2, A3, B), and a list of various lots (“Lot ID by Day”).

[0275] In certain embodiments, data analytics interfaces may include interactive graphical widgets that allow a user to customize and/or toggle between different styles and variables plotted in the dynamic chart. For example, the example interface shown in FIG. 38G includes several sections of graphical widgets, including a Variable Viewing Mode section with a toggle (“Single”/”Multi”) that allows a user to view individual process metrics separately or multiple metrics simultaneously. A Group by process version section includes a toggle (“Yes”/”No”) that allows a user to select whether or not they wish to cluster data according to different process iterations or conditions. An In-process Analytics section includes several selectable widgets through which a user can interact to select various cellular metrics such as percentages of B cells, Monocytes, NK cells, viability, etc., for inclusion in the visualization. There are also absolute number metrics like viable cells and total nucleated cells (TNC), along with an option to include/exclude red blood cells (RBCs). A Computed Metrics section allows for selection of certain computed metrics (e.g., automatically computed, by the processor), such as a total number of NK cells, based on raw data.

[0276] A data analytics interface may also include one or more dynamic charts, such as a cell journey chart shown in FIG. 38G. The particular chart shown in FIG. 38G plots values of the selected metrics over various process unit operations, from "Post Thaw" to "Post Harvest." Each line represents a lot or batch (as indicated by "Lot ID by Day"), showing the progression of a particular metric through the process.

[0277] FIGs. 21A-21J show various versions of data analytics views providing cell data and illustrating, in certain embodiments, impact of different user selection and control via graphical widgets as described herein. FIG. 38H shows two graphs plotting cell count and cell viability metrics, across various unit operations on a particular day.

[0278] In certain embodiments a dynamic chart is interactive, allowing users to select data points directly on the graph, facilitating complex process tracking, for example as illustrated in FIGs. 21A and 21B. This interactivity implies that users can visualize the progression without needing prior data harmonization or processing, which can be especially useful in real-time monitoring or when working with raw data.

[0279] Accordingly, the interactive “cell journey” chart shown in FIG. 38G provides a visual representation of cell journey across multiple lots, highlighting trends, deviations, and process consistency, which are essential for process understanding, control, and optimization.

[0280] In certain embodiments, interactive data selection may be used to generate and display other styles of data analytics interfaces, such patient tiles views, various other Cell Data Views, Swimmer’s chart views, Release Metrics and Characterization views, Starplots, etc. as described herein and illustrated in FIGs. 17A through 25F.

[0281] Among other things, data analytics views of the present provide a deep dive into the manufacturing processes and outputs (e.g., cell processing data), with robust data selection and visualization tools to aid in process analysis and decision-making in a biotechnological or pharmaceutical manufacturing context. iii. Comparison and Alignment of Multiple Processes

[0282] In certain embodiments, graph-based visualization tools of the present disclosure include technologies for automatic comparison and alignment of multiple manufacturing processes. Among other things, this functionality is facilitates understanding the interplay between different manufacturing processes or the same process under different conditions.

[0283] Turning again to FIG. 37, in certain embodiments, a user may select one or more additional processes 3732, to be compared with an initial selected and rendered process. Graph-based visualization tools of the present disclosure may then render and align and/or overlay additional process graphs 3734, each representing an additional selected manufacturing process, for comparison.

[0284] FIG. 38I shows an example screenshot produced via the techniques described herein. The screenshot shows multiple (three) overlaid and aligned process graphs, each representing a similar sequence of unit operations across a timeline of days. These multiple process graphs may represent different experimental runs and/or batches in a manufacturing process. The screenshot illustrates the result of applying the described techniques, displaying three overlaid and aligned process graphs. Each graph represents a sequence of unit operations over a timeline of days. These graphs represent different experimental runs or batches in a manufacturing process, allowing for easy comparison and analysis of these separate activities over the same time period. Comparing multiple graphs in this manner allows users to, among other things:

[0285] (i) Identify patterns and trends: In certain embodiments, by overlaying graphs, user can easily spot common trends or patterns across different datasets or time periods.

[0286] (ii) Evaluate consistency and variability: In certain embodiments, comparing graphs helps assess the consistency of processes or experiments and identify any variability or anomalies. [0287] (iii) Benchmark performance: In certain embodiments, graphs may be used to represent different batches or experimental runs, allowing a user to compare them to determine which one performed better against certain metrics.

[0288] (iv) Understand Relationships: In certain embodiments, seeing how different variables interact over time can help you understand the relationships between them.

[0289] (v) Make Informed Decisions: In certain embodiments, the clear comparisons facilitated via tools described herein make it easier to make decisions based on empirical data, such as improving processes or replicating successful experiments.

[0290] Among other things, process comparison and alignments tools provided herein can programmatically overlay multiple graphs and perform a comparative analysis of their structure and data points. For example, overlaying multiple graphs allows for direct visual comparison of the different experimental runs or process batches. In certain embodiments, by analyzing structures of overlaid graphs, tools of the present disclosure may (e.g., automatically) identify differences and similarities between one or more processes, and visually highlight them via the rendered graphs. For example, if one process deviates at a certain unit operation, process comparison and alignment tools described herein may detect and flag this variation, for example, via variations in icon types, sizes, colors, etc. used to represent nodes. For example, in FIG. 38I process variations are flagged as enlarged color- coded (orange) circles.

[0291] Additionally or alternatively, in certain embodiments, process comparison and alignment tools of the present disclosure may (e.g., automatically) compare data points from different graphs corresponding to different selected processes. For example, systems and methods of the present disclosure may automatically evaluate whether certain data points are consistent across all processes or if there are outliers representing unexpected results and/or deviations outside a particular desired tolerance. Metrics such as means, medians, standard deviations, variance, quartiles, and the like, may be determined across selected processes and/or reference processes (e.g., stored in a database) and individual datapoints from particular processes compared with the metrics to determine whether they should be flagged, e.g., based on whether they fall outside one or more standard deviations, above or below particular quartiles, etc. Such datapoints may be visually highlighted, for example via variations in icon types, sizes, colors, etc. used to represent nodes.

[0292] In certain embodiments, e.g., following data comparison, data from points corresponding to different processes may be extracted to create and export a harmonized dataset 3736. This harmonized dataset can then be used for further analysis, such as statistical testing or predictive modeling. For example, a harmonized dataset may be used as input for mathematical models that can predict outcomes, simulate different scenarios, or optimize the process. These models may be used to facilitate an understanding impact of different unit operations on the overall process and in making data-driven decisions to improve it. Among other things, insights gained from mathematical modeling can be applied to refine the process, improve yields, or enhance quality. By understanding where deviations occur and their impact, process engineers or scientists can implement precise adjustments. Approaches such as these may be especially valuable in fields like biotechnology, pharmaceuticals, and chemical engineering, where process control and optimization are important for ensuring product quality and efficiency.

D. Experimental process design and data collection

[0293] Turning to FIGs. 39A-39D, in certain embodiments, CMC technologies of the present disclosure include experimental process design and data collection GUI for facilitating design and management of manufacturing processes for production of pharmaceutical products. Among other things, as illustrated in FIG. 39 A, an experimental process design and data collection GUI 3906 may receive and/or access data from one or more instruments used to perform various unit operations and/or a database, and render them in an informative and visually convenient manner for one or more users 3910. Experimental process design and data collection GUI 3906 may, additionally or alternatively, receive input from users 3910, such as experiment control parameters, data analysis, and update database 3904 and/or parameters of unit operation instruments 3902. Data may be rendered for and/or received from users 3910 via various graphical widgets and/or sub-portions of GUI 3906, which may be displayed e.g., as separate panels or sections within a single window, multiple sub-windows, and the like. These may include, for example, one or more of: (i) a real-time data display panel comprising graphical rendering of data obtained from and/or input to one or more connected devices used (e.g., to perform unit operations and/or collect measurements) during the particular manufacturing process; (ii) a process design display panel comprising a graphical rendering of one or more unit operations performed during the manufacturing processes (e.g., as linked tiles); (iii) a data input and calculations panel comprising a graphical rendering of a plurality of fields (e.g., textual input boxes) for input of raw data and corresponding calculations; and (iv) a material preparation and data calculations panel comprising a graphical rendering of a plurality of input fields and/or output calculations corresponding to material preparation inputs and calculations, as described in further detail herein. i. Metadata and Real-Time Display

[0294] FIG. 39B shows a screenshot of an example format of GUI 3906, helpful for, among other things, metadata review and real time data display. The GUI layout in FIG. 39B includes a real-time data display panel occupying a top portion of the window, a data input and calculations panel occupying a middle portion of the window, and a process design display panel occupying a bottom portion of the window.

[0295] In certain embodiments, a real-time data display panel that displays real-time data is included. It is set up to receive and show data that is dynamically updated, from connected devices or operator input resulting from execution of the experimental process. For example, the screenshot in FIG. 39B shows elements such as 'Plasmatherm 3x10', 'PRODIGY', and 'PL I20', representing equipment and/or processes with which it may interface to generate real-time data metrics.

[0296] The lower section of the interface is dedicated to a process design display panel for design of the experimental process itself, and the collection of metadata. It outlines a series of unit operations from 'Starting Material' to 'Freeze', suggesting a workflow for material handling and processing. Each unit operation seems to be associated with data input fields, allowing the user to enter and track information such as various unit operations, providing for tracking and managing the use of specific materials and samples. The process flow is visually supported by icons and connecting lines, enhancing the user's ability to follow and manage the experimental protocol. ii. Automated In-Process Calculation and Interface

[0297] FIG. 39C shows a screenshot of an example format of GUI 3906, helpful for, among other things, automated in-process calculations. The GUI layout in FIG. 39C includes a real-time data display panel occupying a top portion of the window, a data input and calculations panel occupying a middle portion of the window, and a process design display panel occupying a bottom portion of the window. The display is similar to that shown in FIG. 39B, but with a “Data Calculations” option selected for the middle portion, as opposed to “Data Input.”

[0298] Data input and calculations panel is tailored for automated in-process calculations, likely providing users with real-time computational support for their experimental data. This section is populated with fields for the input of raw data and its corresponding calculations. The fields include a timestamp, live and dead cell counts, sample volume, and viability percentage, relevant for cell culture or biological sample analysis. It also features an area for 'Raw Metadata', which may be used handling detailed manufacturing process metadata. It includes a calculator and a selection tool for different well plate formats, relevant for various experimental setups and ability to adapt to different data input requirements.

[0299] A 'TOOLS' section may comprise icons for different functions or modules within the software, such as data input, calculations, and experiment configurations. Icons may represent real instruments, e.g., which may be connected to provide real-time data display.

[0300] A bottom portion of the GUI window again shows a process design display panel. Each unit operation in the process flow is paired with interactive elements, such as drop-down menus or input fields, to document and track the progression of materials through the experimental process. iii. Material Preparation and Data Calculations

[0301] FIG. 39D shows a screenshot of an example format of GUI 3906, helpful for, among other things, materials preparation and data calculations. The layout mirrors that in FIGs. 39B and 39C, but with the middle panel now showing a material preparation and data calculations panel.

[0302] Material preparation and data calculations panel displays a table for material preparation calculations, facilitating user management of experiments that require precise measurements and tracking of reagents and materials. The table provides fields for the input of various data points such as stock concentration, volume per vessel, and number of vessels, which are essential for accurately preparing experimental materials. In certain embodiments, GUI 3906 may use color-coded warnings, such as "Do not modify grey or yellow cells", guide the user to interact with the software correctly, suggesting built-in safeguards or validation rules to ensure data integrity.

[0303] In certain embodiments, GUI 3906 may be used for multi -well experiments, with FIG. 39D showing detailed input fields and calculated data for different time points, such as Day 0, Day 7, and Day 11. The table includes comprehensive data such as experimental concentrations, volumes per vessel, and total volumes, allowing for intricate management of experimental conditions over time.

[0304] Accordingly, among other things, various combinations of visual elements and the interactive nature of the interface as described herein provide a streamlined and efficient workflow for laboratory experiments.

[0305] In particular, among other things, the GUI shown in FIGs. 39A-D combines a static process designer chart with dynamic data display, input, and calculation functionality that allows users to readily inspect and analyze data that is being collected and/or input in various unit operations over complex manufacturing processes in near real-time. In particular, users may select linked tiles displayed in the lower portion of the interface to select particular unit operations. The upper, data display, input and/or calculation portion of the interface then updates to reflect data associated with the particular selected unit operation, as guided by custom ontologies stored, e.g., in the knowledge base described herein. This allows users to read and manipulate data in real time, ensure data is being collected completely and timely, and enter in missing data where needed. This approach facilitates and speeds up complex and time-consuming data management activities in the context of pharmaceutical product manufacturing.

E. Software, Computer System., and Network Environment

[0306] Certain embodiments described herein make use of computer algorithms in the form of software instructions executed by a computer processor. In certain embodiments, the software instructions include a machine learning module, also referred to herein as artificial intelligence software. As used herein, a machine learning module refers to a computer implemented process (e.g., a software function) that implements one or more specific machine learning algorithms, such as an artificial neural network (ANN), random forest, decision trees, support vector machines, and the like, in order to determine, for a given input, one or more output values. In certain embodiments, the input comprises alphanumeric data which can include numbers, words, phrases, or lengthier strings, for example. In certain embodiments, the one or more output values comprise values representing numeric values, words, phrases, or other alphanumeric strings. In certain embodiments, the one or more output values comprise an identification of one or more response strings (e.g., selected from a database).

[0307] For example, a machine learning module may receive as input a textual string (e.g., entered by a human user, for example) and generate various outputs. For example, the machine learning module may automatically analyze the input alphanumeric string(s) to determine output values classifying a content of the text (e.g., an intent), e.g., as in natural language understanding (NLU). In certain embodiments, a textual string is analyzed to generate and/or retrieve an output alphanumeric string. For example, a machine learning module may be (or include) natural language processing (NLP) software.

[0308] In certain embodiments, machine learning modules implementing machine learning techniques are trained, for example using datasets that include categories of data described herein. Such training may be used to determine various parameters of machine learning algorithms implemented by a machine learning module, such as weights associated with layers in neural networks. In certain embodiments, once a machine learning module is trained, e.g., to accomplish a specific task such as identifying certain response strings, values of determined parameters are fixed and the (e.g., unchanging, static) machine learning module is used to process new data (e.g., different from the training data) and accomplish its trained task without further updates to its parameters (e.g., the machine learning module does not receive feedback and/or updates). In certain embodiments, machine learning modules may receive feedback, e.g., based on user review of accuracy, and such feedback may be used as additional training data, to dynamically update the machine learning module. In certain embodiments, two or more machine learning modules may be combined and implemented as a single module and/or a single software application. In certain embodiments, two or more machine learning modules may also be implemented separately, e.g., as separate software applications. A machine learning module may be software and/or hardware. For example, a machine learning module may be implemented entirely as software, or certain functions of an ANN module may be carried out via specialized hardware (e.g., via an application specific integrated circuit (ASIC)).

[0309] As shown in FIG. 40, an implementation of a network environment 4000 for use in providing systems, methods, and architectures as described herein is shown and described. In brief overview, referring now to FIG. 40, a block diagram of an exemplary cloud computing environment 4000 is shown and described. The cloud computing environment 4000 may include one or more resource providers 4002a, 4002b, 4002c (collectively, 4002). Each resource provider 4002 may include computing resources. In some implementations, computing resources may include any hardware and/or software used to process data. For example, computing resources may include hardware and/or software capable of executing algorithms, computer programs, and/or computer applications. In some implementations, exemplary computing resources may include application servers and/or databases with storage and retrieval capabilities. Each resource provider 4002 may be connected to any other resource provider 4002 in the cloud computing environment 4000. In some implementations, the resource providers 4002 may be connected over a computer network 4008. Each resource provider 4002 may be connected to one or more computing device 4004a, 4004b, 4004c (collectively, 4004), over the computer network 4008. [0310] The cloud computing environment 4000 may include a resource manager 4006. The resource manager 4006 may be connected to the resource providers 4002 and the computing devices 4004 over the computer network 4008. In some implementations, the resource manager 4006 may facilitate the provision of computing resources by one or more resource providers 4002 to one or more computing devices 4004. The resource manager 4006 may receive a request for a computing resource from a particular computing device 4004. The resource manager 4006 may identify one or more resource providers 4002 capable of providing the computing resource requested by the computing device 4004. The resource manager 4006 may select a resource provider 4002 to provide the computing resource. The resource manager 4006 may facilitate a connection between the resource provider 4002 and a particular computing device 4004. In some implementations, the resource manager 4006 may establish a connection between a particular resource provider 4002 and a particular computing device 4004. In some implementations, the resource manager 4006 may redirect a particular computing device 4004 to a particular resource provider 4002 with the requested computing resource.

[0311] FIG. 41 shows an example of a computing device 4100 and a mobile computing device 4150 that can be used to implement the techniques described in this disclosure. The computing device 4100 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The mobile computing device 4150 is intended to represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart-phones, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to be limiting.

[0312] The computing device 4100 includes a processor 4102, a memory 4104, a storage device 4106, a high-speed interface 4108 connecting to the memory 4104 and multiple high-speed expansion ports 4110, and a low-speed interface 4112 connecting to a low-speed expansion port 4114 and the storage device 4106. Each of the processor 4102, the memory 4104, the storage device 4106, the high-speed interface 4108, the high-speed expansion ports 4110, and the low-speed interface 4112, are interconnected using various busses, and may be mounted on a common motherboard or in other manners as appropriate. The processor 4102 can process instructions for execution within the computing device 4100, including instructions stored in the memory 4104 or on the storage device 4106 to display graphical information for a GUI on an external input/output device, such as a display 4116 coupled to the high-speed interface 4108. In other implementations, multiple processors and/or multiple buses may be used, as appropriate, along with multiple memories and types of memory. Also, multiple computing devices may be connected, with each device providing portions of the necessary operations (e.g., as a server bank, a group of blade servers, or a multi-processor system). Thus, as the term is used herein, where a plurality of functions are described as being performed by “a processor”, this encompasses embodiments wherein the plurality of functions are performed by any number of processors (one or more) of any number of computing devices (one or more). Furthermore, where a function is described as being performed by “a processor”, this encompasses embodiments wherein the function is performed by any number of processors (one or more) of any number of computing devices (one or more) (e.g., in a distributed computing system).

[0313] The memory 4104 stores information within the computing device 4100. In some implementations, the memory 4104 is a volatile memory unit or units. In some implementations, the memory 4104 is a non-volatile memory unit or units. The memory 4104 may also be another form of computer-readable medium, such as a magnetic or optical disk.

[0314] The storage device 4106 is capable of providing mass storage for the computing device 4100. In some implementations, the storage device 4106 may be or contain a computer-readable medium, such as a floppy disk device, a hard disk device, an optical disk device, or a tape device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations. Instructions can be stored in an information carrier. The instructions, when executed by one or more processing devices (for example, processor 4102), perform one or more methods, such as those described above. The instructions can also be stored by one or more storage devices such as computer- or machine-readable mediums (for example, the memory 4104, the storage device 4106, or memory on the processor 4102). [0315] The high-speed interface 4108 manages bandwidth-intensive operations for the computing device 4100, while the low-speed interface 4112 manages lower bandwidth- intensive operations. Such allocation of functions is an example only. In some implementations, the high-speed interface 4108 is coupled to the memory 4104, the display 4116 (e.g., through a graphics processor or accelerator), and to the high-speed expansion ports 4110, which may accept various expansion cards (not shown). In the implementation, the low-speed interface 4112 is coupled to the storage device 4106 and the low-speed expansion port 4114. The low-speed expansion port 4114, which may include various communication ports (e.g., USB, Bluetooth®, Ethernet, wireless Ethernet) may be coupled to one or more input/output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter.

[0316] The computing device 4100 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a standard server 4120, or multiple times in a group of such servers. In addition, it may be implemented in a personal computer such as a laptop computer 4122. It may also be implemented as part of a rack server system 4124. Alternatively, components from the computing device 4100 may be combined with other components in a mobile device (not shown), such as a mobile computing device 4150. Each of such devices may contain one or more of the computing devices 4100 and the mobile computing device 4150, and an entire system may be made up of multiple computing devices communicating with each other.

[0317] The mobile computing device 4150 includes a processor 4152, a memory 4164, an input/output device such as a display 4154, a communication interface 4166, and a transceiver 4168, among other components. The mobile computing device 4150 may also be provided with a storage device, such as a micro-drive or other device, to provide additional storage. Each of the processor 4152, the memory 4164, the display 4154, the communication interface 4166, and the transceiver 4168, are interconnected using various buses, and several of the components may be mounted on a common motherboard or in other manners as appropriate.

[0318] The processor 4152 can execute instructions within the mobile computing device 4150, including instructions stored in the memory 4164. The processor 4152 may be implemented as a chipset of chips that include separate and multiple analog and digital processors. The processor 4152 may provide, for example, for coordination of the other components of the mobile computing device 4150, such as control of user interfaces, applications run by the mobile computing device 4150, and wireless communication by the mobile computing device 4150.

[0319] The processor 4152 may communicate with a user through a control interface 4158 and a display interface 4156 coupled to the display 4154. The display 4154 may be, for example, a TFT (Thin-Film-Transistor Liquid Crystal Display) display or an OLED (Organic Light Emitting Diode) display, or other appropriate display technology. The display interface 4156 may comprise appropriate circuitry for driving the display 4154 to present graphical and other information to a user. The control interface 4158 may receive commands from a user and convert them for submission to the processor 4152. In addition, an external interface 4162 may provide communication with the processor 4152, so as to enable near area communication of the mobile computing device 4150 with other devices. The external interface 4162 may provide, for example, for wired communication in some implementations, or for wireless communication in other implementations, and multiple interfaces may also be used.

[0320] The memory 4164 stores information within the mobile computing device 4150. The memory 4164 can be implemented as one or more of a computer-readable medium or media, a volatile memory unit or units, or a non-volatile memory unit or units. An expansion memory 4174 may also be provided and connected to the mobile computing device 4150 through an expansion interface 4172, which may include, for example, a SIMM (Single In Line Memory Module) card interface. The expansion memory 4174 may provide extra storage space for the mobile computing device 4150, or may also store applications or other information for the mobile computing device 4150. Specifically, the expansion memory 4174 may include instructions to carry out or supplement the processes described above, and may include secure information also. Thus, for example, the expansion memory 4174 may be provide as a security module for the mobile computing device 4150, and may be programmed with instructions that permit secure use of the mobile computing device 4150. In addition, secure applications may be provided via the SIMM cards, along with additional information, such as placing identifying information on the SIMM card in a non-hackable manner.

[0321] The memory may include, for example, flash memory and/or NVRAM memory (non-volatile random access memory), as discussed below. In some implementations, instructions are stored in an information carrier. The instructions, when executed by one or more processing devices (for example, processor 4152), perform one or more methods, such as those described above. The instructions can also be stored by one or more storage devices, such as one or more computer- or machine-readable mediums (for example, the memory 4164, the expansion memory 4174, or memory on the processor 4152). In some implementations, the instructions can be received in a propagated signal, for example, over the transceiver 4168 or the external interface 4162.

[0322] The mobile computing device 4150 may communicate wirelessly through the communication interface 4166, which may include digital signal processing circuitry where necessary. The communication interface 4166 may provide for communications under various modes or protocols, such as GSM voice calls (Global System for Mobile communications), SMS (Short Message Service), EMS (Enhanced Messaging Service), or MMS messaging (Multimedia Messaging Service), CDMA (code division multiple access), TDMA (time division multiple access), PDC (Personal Digital Cellular), WCDMA (Wideband Code Division Multiple Access), CDMA2000, or GPRS (General Packet Radio Service), among others. Such communication may occur, for example, through the transceiver 4168 using a radio-frequency. In addition, short-range communication may occur, such as using a Bluetooth®, Wi-Fi™, or other such transceiver (not shown). In addition, a GPS (Global Positioning System) receiver module 4170 may provide additional navigation- and location-related wireless data to the mobile computing device 4150, which may be used as appropriate by applications running on the mobile computing device 4150.

[0323] The mobile computing device 4150 may also communicate audibly using an audio codec 4160, which may receive spoken information from a user and convert it to usable digital information. The audio codec 4160 may likewise generate audible sound for a user, such as through a speaker, e.g., in a handset of the mobile computing device 4150. Such sound may include sound from voice telephone calls, may include recorded sound (e.g., voice messages, music files, etc.) and may also include sound generated by applications operating on the mobile computing device 4150.

[0324] The mobile computing device 4150 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a cellular telephone 4180. It may also be implemented as part of a smart-phone 4182, personal digital assistant, or other similar mobile device.

[0325] Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0326] These computer programs (also known as programs, software, software applications or code) include machine instructions for a programmable processor, and can be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the terms machine-readable medium and computer-readable medium refer to any computer program product, apparatus and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine- readable medium that receives machine instructions as a machine-readable signal. The term machine-readable signal refers to any signal used to provide machine instructions and/or data to a programmable processor.

[0327] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0328] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0329] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0330] In some implementations, certain modules described herein can be separated, combined or incorporated into single or combined modules. Any modules depicted in the figures are not intended to limit the systems described herein to the software architectures shown therein.

[0331] Elements of different implementations described herein may be combined to form other implementations not specifically set forth above. Elements may be left out of the processes, computer programs, databases, etc. described herein without adversely affecting their operation. In addition, the logic flows depicted in the figures do not require the particular order shown, or sequential order, to achieve desirable results. Various separate elements may be combined into one or more individual elements to perform the functions described herein.

[0332] While the invention has been particularly shown and described with reference to specific preferred embodiments, it should be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims

What is claimed is:

1. A method of using heterogeneous, structured data of an enterprise in the development and/or production of a pharmaceutical product (e.g., a cellular therapy product, e.g., Natural Killer (NK) cells, T cells, iPS-derived CAR T cells, Gamma-Delta (GD) T cells, or stem cells), the method comprising:

(a) receiving, by a processor of a computing device, a user query via a portal (e.g., a web-based portal), said query related to one or more of (i) to (iii) as follows: (i) the design of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product), (ii) the operation of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product) (e.g., process monitoring and/or process control), and (iii) the modeling of a manufacturing process for production of the pharmaceutical product (e.g., the cell therapy product);

(b) conveying the user query to a mediator of a view-based data integration system (VDIS) to produce a response to the user query, wherein the VDIS accesses (e.g., via a federated server) multiple data sources with heterogeneous data formats and retrieves integrated results (e.g., combining data from multiple sources and resolving one or more inconsistencies), wherein the response to the user query comprises the integrated results; and

(c) graphically rendering the response to the user query.

2. The method of claim 1, wherein the multiple data sources accessed by the VDIS comprises one or more of (i) to (viii) as follows: (i) raw exploratory oncology and/or cellular therapy data, (ii) processed exploratory oncology and/or cellular therapy data (e.g., results), (iii) cellular therapy product characteristics, (iv) raw pharmacokinetics data, (v) raw primary and/or secondary biologic endpoint data, (vi) manufacturing process protocols, (vii) manufacturing unit operations (device) data, and (viii) analytical device data.

3. The method of claim 1 or 2, wherein step (c) comprises updating a process monitoring graphical display (e.g., monitoring dashboard) with the response to the user query in real-time (e.g., near real-time).

4. The method of any one of the preceding claims, wherein the multiple data sources accessed by the VDIS comprise live data (e.g., data that is updated in real-time).

5. The method of any one of the preceding claims, wherein step (c) comprises graphically rendering a digital page comprising multiple sentences and/or paragraphs of text, said digital page also comprising user-interactive data (e.g., tiled data) related to said text, said data updated to reflect the response to the user query.

6. The method of any one of the preceding claims, wherein the view-based data integration system comprises a both-as-view (BAV) [aka global and local as view (GLAV)] back-end infrastructure.

7. The method of any one of the preceding claims, wherein the view-based data integration system comprises a global -as-view (GAV) back-end infrastructure and/or a local- as-view (LAV) back-end infrastructure.

8. The method of any one of the preceding claims, wherein the mediator converts the user query into a plurality of source-specific queries and sends the source-specific queries to one or more wrappers for execution, producing the response to the query.

9. The method of any one of claims 6 to 8, wherein the back-end infrastructure comprises a plurality of sources comprising heterogeneous structured data that are integrated into a unified view.

10. The method of any one of the preceding claims, wherein the method uses a graph- based, real-time digitalization and contextualization engine.

11. The method of any one of the preceding claims, wherein the multiple data sources with heterogeneous data formats accessed by the VDIS comprises at least one data source whose data is automatically harmonized at point of data collection.

12. The method of claim 11, wherein the at least one data source has its data automatically harmonized by restricting data entry to a plurality of predetermined fields and/or values.

13. The method of any one of the preceding claims, wherein step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., a process director display) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a step in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the process step represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS.

14. The method of any one of the preceding claims, wherein step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., a process designer) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a unit operation in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS, wherein the one or more blocks may be linked together in the creation of a new experimental and/or manufacturing process comprising the plurality of unit operations represented by the linked blocks, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the unit operation represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS.

15. The method of any one of the preceding claims, wherein step (c) comprises graphically rendering the response to the query via a graphical user interface (e.g., patient tiles) comprising a plurality of tiles (e.g., a type of graphical widget), wherein each tile represents a particular subject (e.g., a patient in a clinical trial) whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS (e.g., wherein the tiles have different colors, shading, line-styles, or the like to visually convey data pertaining to the subjects, e.g., to convey clinical response), wherein the one or more tiles are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the subject represented by the particular tile, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS.

16. The method of any one of the preceding claims, wherein step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., substantially as rendered in FIGS. 4A to 34J).

17. A method of using data of an enterprise in the development and/or production of a pharmaceutical product (e.g., a cellular therapy product, e.g., Natural Killer (NK) cells, T cells, iPS -derived CAR T cells, Gamma-Delta (GD) T cells, or stem cells), the method comprising:

(a) receiving, by a processor of a computing device, a user query via a portal (e.g., a web-based portal), said query related to one or more of (i) to (iii) as follows: (i) the design of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product), (ii) the operation of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product) (e.g., process monitoring and/or process control), and (iii) the modeling of a manufacturing process for production of the pharmaceutical product (e.g., the cell therapy product);

(b) conveying the user query to a database management system to produce a response to the user query, wherein the database management system accesses (e.g., via a federated server) multiple data sources and retrieves results (e.g., combining data from multiple sources and resolving one or more inconsistencies to produce integrated results), wherein the response to the user query comprises the results; and

(c) graphically rendering the response to the user query, wherein the multiple data sources accessed by the database management system comprise at least one data source whose data is automatically harmonized at point of data collection by restriction of data entry to a plurality of predetermined fields and/or values.

18. The method of claim 17, wherein the multiple data sources accessed by the database management system comprises one or more of (i) to (viii) as follows: (i) raw exploratory oncology and/or cellular therapy data, (ii) processed exploratory oncology and/or cellular therapy data (e.g., results), (iii) cellular therapy product characteristics, (iv) raw pharmacokinetics data, (v) raw primary and/or secondary biologic endpoint data, (vi) manufacturing process protocols, (vii) manufacturing unit operations (device) data, and (viii) analytical device data.

19. The method of claim 17 or 18, wherein step (c) comprises updating a process monitoring graphical display (e.g., monitoring dashboard) with the response to the user query in real-time (e.g., near real-time).

20. The method of any one of claims 17 to 19, wherein the multiple data sources accessed by the database management system comprise live data (e.g., data that is updated in real- time).

21. The method of any one of claims 17 to 20, wherein step (c) comprises graphically rendering a digital page comprising multiple sentences and/or paragraphs of text, said digital page also comprising user-interactive data (e.g., tiled data) related to said text, said data updated to reflect the response to the user query.

22. The method of any one of claims 17 to 21, wherein the method uses a graph-based, real-time digitalization and contextualization engine.

23. The method of any one of claims 17 to 22, wherein step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., a process director display) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a step in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the process step represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system.

24. The method of any one of claims 17 to 23, wherein step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., a process designer) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a unit operation in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system, wherein the one or more blocks may be linked together in the creation of a new experimental and/or manufacturing process comprising the plurality of unit operations represented by the linked blocks, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the unit operation represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system.

25. The method of any one of claims 17 to 24, wherein step (c) comprises graphically rendering the response to the query via a graphical user interface (e.g., patient tiles) comprising a plurality of tiles (e.g., a type of graphical widget), wherein each tile represents a particular subject (e.g., a patient in a clinical trial) whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system (e.g., wherein the tiles have different colors, shading, line-styles, or the like to visually convey data pertaining to the subjects, e.g., to convey clinical response), wherein the one or more tiles are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the subject represented by the particular tile, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system.

26. The method of any one of claims 17 to 25, wherein step (c) comprises graphically rendering the response to the user query via a graphical user interface (e.g., substantially as rendered in FIGS. 4 A to 34J).

27. A system for using heterogeneous, structured data of an enterprise in the development and/or production of a pharmaceutical product (e.g., a cellular therapy product, e.g., Natural Killer (NK) cells, T cells, iPS-derived CAR T cells, Gamma-Delta (GD) T cells, or stem cells), the system comprising: a processor of a computing device; and a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:

(a) receive a user query via a portal (e.g., a web-based portal), said query related to one or more of (i) to (iii) as follows: (i) the design of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product), (ii) the operation of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product) (e.g., process monitoring and/or process control), and (iii) the modeling of a manufacturing process for production of the pharmaceutical product (e.g., the cell therapy product);

(b) convey the user query to a mediator of a view-based data integration system (VDIS) to produce a response to the user query, wherein the VDIS accesses (e.g., via a federated server) multiple data sources with heterogeneous data formats and retrieves integrated results (e.g., combining data from multiple sources and resolving one or more inconsistencies), wherein the response to the user query comprises the integrated results; and

(c) graphically render the response to the user query.

28. The system of claim 27, wherein the multiple data sources accessed by the VDIS comprises one or more of (i) to (viii) as follows: (i) raw exploratory oncology and/or cellular therapy data, (ii) processed exploratory oncology and/or cellular therapy data (e.g., results), (iii) cellular therapy product characteristics, (iv) raw pharmacokinetics data, (v) raw primary and/or secondary biologic endpoint data, (vi) manufacturing process protocols, (vii) manufacturing unit operations (device) data, and (viii) analytical device data.

29. The system of claim 27 or 28, wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) update a process monitoring graphical display (e.g., monitoring dashboard) with the response to the user query in real-time (e.g., near real-time).

30. The system of any one of claims 27 to 29, wherein the multiple data sources accessed by the VDIS comprise live data (e.g., data that is updated in real-time).

31. The system of any one of claims 27 to 30, wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render a digital page comprising multiple sentences and/or paragraphs of text, said digital page also comprising user-interactive data (e.g., tiled data) related to said text, said data updated to reflect the response to the user query.

32. The system of any one of claims 27 to 31, wherein the view-based data integration system comprises a both-as-view (BAV) [aka global and local as view (GLAV)] back-end infrastructure.

33. The system of any one of claims 27 to 32, wherein the view-based data integration system comprises a global-as-view (GAV) back-end infrastructure and/or a local -as-view (LAV) back-end infrastructure.

34. The system of any one of claims 27 to 33, wherein the mediator converts the user query into a plurality of source-specific queries and sends the source-specific queries to one or more wrappers for execution, producing the response to the query.

35. The system of any one of claims 32 to 34, wherein the back-end infrastructure comprises a plurality of sources comprising heterogeneous structured data that are integrated into a unified view.

36. The system of any one of claims 27 to 35, wherein the system uses a graph-based, real-time digitalization and contextualization engine.

37. The system of any one of claims 27 to 36, wherein the multiple data sources with heterogeneous data formats accessed by the VDIS comprises at least one data source whose data is automatically harmonized at point of data collection.

38. The system of claim 37, wherein the at least one data source has its data automatically harmonized by restricting data entry to a plurality of predetermined fields and/or values.

39. The system of any one of claims 27 to 38, wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., a process director display) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a step in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the process step represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS.

40. The system of any one of claims 27 to 39, wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., a process designer) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a unit operation in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS, wherein the one or more blocks may be linked together in the creation of a new experimental and/or manufacturing process comprising the plurality of unit operations represented by the linked blocks, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the unit operation represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS.

41. The system of any one of claims 27 to 40, wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the query via a graphical user interface (e.g., patient tiles) comprising a plurality of tiles (e.g., a type of graphical widget), wherein each tile represents a particular subject (e.g., a patient in a clinical trial) whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the VDIS (e.g., wherein the tiles have different colors, shading, line- styles, or the like to visually convey data pertaining to the subjects, e.g., to convey clinical response), wherein the one or more tiles are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the subject represented by the particular tile, wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS.

42. The system of any one of claims 27 to 41, wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., substantially as rendered in FIGS. 4A to 34J).

43. A system of using data of an enterprise in the development and/or production of a pharmaceutical product (e.g., a cellular therapy product, e.g., Natural Killer (NK) cells, T cells, iPS-derived CAR T cells, Gamma-Delta (GD) T cells, or stem cells), the system comprising: a processor of a computing device; and a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:

(a) receive a user query via a portal (e.g., a web-based portal), said query related to one or more of (i) to (iii) as follows: (i) the design of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product), (ii) the operation of a manufacturing process for production of the pharmaceutical product (e.g., the cellular therapy product) (e.g., process monitoring and/or process control), and (iii) the modeling of a manufacturing process for production of the pharmaceutical product (e.g., the cell therapy product);

(b) convey the user query to a database management system to produce a response to the user query, wherein the database management system accesses (e.g., via a federated server) multiple data sources and retrieves results (e.g., combining data from multiple sources and resolving one or more inconsistencies to produce integrated results), wherein the response to the user query comprises the results; and

(c) graphically render the response to the user query, wherein the multiple data sources accessed by the database management system comprise at least one data source whose data is automatically harmonized at point of data collection by restriction of data entry to a plurality of predetermined fields and/or values.

44. The system of claim 43, wherein the multiple data sources accessed by the database management system comprises one or more of (i) to (viii) as follows: (i) raw exploratory oncology and/or cellular therapy data, (ii) processed exploratory oncology and/or cellular therapy data (e.g., results), (iii) cellular therapy product characteristics, (iv) raw pharmacokinetics data, (v) raw primary and/or secondary biologic endpoint data, (vi) manufacturing process protocols, (vii) manufacturing unit operations (device) data, and (viii) analytical device data.

45. The system of claim 43 or 44 wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) update a process monitoring graphical display (e.g., monitoring dashboard) with the response to the user query in real-time (e.g., near real-time).

46. The system of any one of claims 43 to 45, wherein the multiple data sources accessed by the database management system comprise live data (e.g., data that is updated in real- time).

47. The system of any one of claims 43 to 46, wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render a digital page comprising multiple sentences and/or paragraphs of text, said digital page also comprising user-interactive data (e.g., tiled data) related to said text, said data updated to reflect the response to the user query.

48. The system of any one of claims 43 to 47, wherein the system uses a graph-based, real-time digitalization and contextualization engine.

49. The system of any one of claims 43 to 48, wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., a process director display) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a step in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch- screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the process step represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system.

50. The system of any one of claims 43 to 49, wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., a process designer) comprising one or more linked blocks (e.g., a type of graphical widget, e.g., tiles), wherein each block represents a unit operation in a particular experimental and/or manufacturing process whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system, wherein the one or more blocks may be linked together in the creation of a new experimental and/or manufacturing process comprising the plurality of unit operations represented by the linked blocks, wherein the one or more blocks are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the unit operation represented by the particular block, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system.

51. The system of any one of claims 43 to 50, wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the query via a graphical user interface (e.g., patient tiles) comprising a plurality of tiles (e.g., a type of graphical widget), wherein each tile represents a particular subject (e.g., a patient in a clinical trial) whose data (e.g., live data) is contained in at least one of the multiple data sources accessed by the database management system (e.g., wherein the tiles have different colors, shading, line-styles, or the like to visually convey data pertaining to the subjects, e.g., to convey clinical response), wherein the one or more tiles are dynamic such that upon a user interaction with a particular block (e.g., via a mouse click or hover, e.g., a tap or other touch- screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the subject represented by the particular tile, wherein the additional data is contained in at least one of the multiple data sources accessed by the database management system.

52. The system of any one of claims 43 to 51, wherein the instructions, when executed by the processor, cause the processor to (e.g., in step (c)) graphically render the response to the user query via a graphical user interface (e.g., substantially as rendered in FIGS. 4A to 34J).

53. A method for facilitating user management of manufacturing processes (e.g., experimental (e.g., lab or pilot scale) processes, developed for/in the design of a manufacturing process; e.g., commercial scale production processes) for production of pharmaceutical products (e.g., cellular therapy products, e.g., biologic drugs) via an interactive manufacturing management graphical user-interface (GUI), the method comprising:

(a) receiving and/or accessing, by a processor of a computing device, manufacturing process data corresponding to a plurality of unit operations in a particular manufacturing process, said data representing (i) actions performed in the plurality of unit operations and/or (ii) information collected for the plurality of unit operations (e.g., information collected before, during, and/or after one or more of the plurality of unit operations is/are performed); and

(b) causing, by the processor, rendering of a graph-based visualization of the particular manufacturing process via the manufacturing management GUI, wherein the graph-based visualization comprises a plurality of interactive nodes [e.g., graphical icons, such as (e.g., color-coded) inter-connected circular icons], each interactive node of the plurality of interactive nodes representing (i) an individual datapoint corresponding to a particular action that is performed in one of the plurality of unit operations and/or (ii) a particular set of information that is collected for a particular one of the plurality of unit operations (e.g., information collected before, during, and/or after the particular unit operation) [e.g., wherein one or more of the interactive nodes are linked (e.g., connected with each other), each link between a first and second interactive node representing a dependency and/or sequence of material and/or data flow (e.g., each link graphically rendered as a line connecting two graphical icons representing nodes)].

54. The method of claim 53, wherein the graph-based visualization comprises a timeline depicting days (e.g., over which the particular manufacturing process is performed) and/or unit operations (e.g., of the particular manufacturing process) [e.g., a vertical or horizontal line, with (e.g., labeled) markings along the line representing days and/or unit operations] and each interactive node of the plurality of interactive nodes is visually associated with a particular one of the days and/or unit operations of the timeline (e.g., positioned, within the graph-based visualization, in proximity to the particular day and/or unit operation, along a same horizonal and/or vertical axis as the particular day and/or unit operation, etc.).

55. The method of claim 53 or 54, wherein the graph-based visualization comprises a base graph corresponding to and representing a baseline version of the manufacturing process along with one or more auxiliary sub-graphs, each sub-graph corresponding to and representing a variation to experimental conditions and/or the baseline version of the manufacturing process [e.g., wherein the one or more auxiliary sub-graphs are displayed below the base graph (e.g., each auxiliary sub-graph comprising one or more icons representing nodes and connecting lines representing links between nodes, representing, in turn, unit operations and material and/or dataflow between them, respectively)].

56. The method of any one of the claims 53 to 55, wherein the plurality of interactive nodes are dynamic such that upon a user interaction with a particular interactive node (e.g., via a mouse click or hover, e.g., a tap or other touch-screen based interaction) a pop-up window (e.g., an expandable pop-up) appears, to convey to a user additional data pertaining to the datapoint represented by the particular interactive node (e.g., wherein the additional data is contained in at least one of the multiple data sources accessed by the VDIS).

57. The method of any one of claims 54 to 56, comprising rendering, for each of one or more data parameters and/or variables being controlled and/or monitored during the particular manufacturing process, a plurality of datapoint indicators, each datapoint indicator representing a collected and/or input value of the data parameter and/or variable at a particular time point and/or unit operation during the particular manufacturing process.

58. The method of claim 57, wherein the plurality of datapoint indicators are color-coded according to whether data are collected, missing, and/or selected for further analysis.

59. The method of any one of claims 57 to 58, comprising: receiving, by the processor, via the GUI, a user selection of at least a portion of the datapoints (e.g., via a user click); and generating, by the processor, an interactive graph plotting values of the selected datapoints.

60. The method of claim 59, wherein the manufacturing process data comprises a plurality of sets of values for the one or more data parameters and/or variables being controlled and/or monitored during the particular manufacturing process, each set of values associated with a distinct lot and/or batch, and wherein the interactive graph comprises a plurality of traces [e.g., lines, collections of points (e.g., as in a scatter plot), series of bars (e.g., as in a bar graph), graphical icons (e.g., as in a pictogram), etc.; e.g., as shown in any of FIGs. 20A-28F], each trace corresponding to and showing progression of the set of values for the particular lot and/or batch with which the set is associated.

61. The method of any one of claims 53 to 60, comprising: receiving and/or accessing, by the processor, additional manufacturing process data corresponding to one or more additional manufacturing processes; and causing, by the processor, rendering of one or more additional graph-based visualizations, each representing a particular one of the one or more additional manufacturing processes within the manufacturing management GUI, wherein the one or more additional graph-based visualizations are aligned and/or overlaid with the graph-based visualization corresponding the particular manufacturing processes.

62. The method of claim 61, wherein rendering the one or more additional graph-based visualizations comprises automatically highlighting deviations between the one or more processes and/or from a reference (e.g., visually rendering nodes and/or lines connecting them that represent unit operations having one or more parameters and/or collected data that (i) differ from those of other processes and/or (ii) deviate from reference values and/or ranges of reference values).

63. The method of any one of claims 61 to 62, comprising generating and outputting a harmonized dataset [e.g., identifying (e.g., automatically and/or based on user input and/or selection) data points that are consistent and/or outliers, and then extracting a portion of the data points (e.g., those identified as consistent) to generate the harmonized dataset] corresponding to the particular manufacturing process and the one or more additional manufacturing processes (e.g., for subsequent mathematical modelling).

64. The method of any one of claims 61 to 63, comprising: receiving, by the processor, via the manufacturing management GUI a user selection of one or more nodes for inclusion in a harmonized dataset and/or a user input of data into one or more nodes of the graph-based visualization and/or the one or more additional graph- based visualizations; and generating, by the processor, based at least in part on the user selection and/or input of data, a harmonized dataset (e.g., a dataset in which the user selected nodes and/or initially stored data is replaced with the user input).

65. A method for facilitating experimental process design and data collection for manufacturing production processes via an interactive GUI, the method comprising:

(a) receiving and/or accessing, by a processor of a computing device, manufacturing process data corresponding to a particular manufacturing process and representing actions (e.g., unit operations in the particular manufacturing process) performed and/or information collected during the particular manufacturing process; and

(b) causing, by the processor, graphical rendering of one or more interactive panels representing the actions and/or information collected during the manufacturing processes, the one or more interactive sub-panels comprising one or more (e.g., up to all) of the following:

(i) a real-time data display panel comprising graphical rendering of data obtained from and/or input to one or more connected devices used (e.g., to perform unit operations and/or collect measurements) during the particular manufacturing process;

(ii) a process design display panel comprising a graphical rendering of one or more unit operations performed during the manufacturing processes (e.g., as linked tiles);

(iii) a data input and calculations panel comprising a graphical rendering of a plurality of fields (e.g., textual input boxes) for input of raw data and corresponding calculations; and

(iv) a material preparation and data calculations panel comprising a graphical rendering of a plurality of input fields and/or output calculations corresponding to material preparation inputs and calculations.

66. The method of claim 65, wherein unit operation comprises causing graphical rendering of the real-time data display panel and dynamically updating the real-time data display panel according to variations in values of parameters input to and/or collected from one or more interconnected devices.

67. The method of claim 65 or claim 66, wherein step (b) comprises: causing, by the processor, graphical rendering of the process design panel, said process design panel comprising one or more selectable icons (e.g., linked tiles), each representing a particular unit operation in the manufacturing process; receiving, by the processor, a user selection of a particular unit operation for data review and/or input via a user interaction with a corresponding one of the one or more selectable icons within the process design panel; and causing, by the processor, updating, so as to reflect data associated with (e.g., collected during and/or input to) the particular unit operation, of one or more of: the real time data display panel, the data input and calculations panel, and the material preparation and data calculations panel [e.g., wherein the updating comprises identifying, within one or more databases (e.g., a knowledge base), a set of data related to the particular unit operation (e.g., and the particular manufacturing process) based on a stored ontology that links unit operations, manufacturing processes, input parameters, and collected data in a relational fashion (e.g., in a hierarchical fashion, e.g., via a knowledge graph)].

68. A system for facilitating user management of manufacturing processes (e.g., experimental (e.g., lab or pilot scale) processes, developed for/in the design of a manufacturing process; e.g., commercial scale production processes) for production of pharmaceutical products (e.g., cellular therapy products, e.g., biologic drugs) via an interactive manufacturing management graphical user-interface (GUI), the system comprising: a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:

(a) receive and/or access manufacturing process data corresponding to a plurality of unit operations in a particular manufacturing process and representing actions performed in the plurality of unit operations manufacturing process and/or information collected for the plurality of unit operations in the particular manufacturing process (e.g., information collected before, during, and/or after one or more of the plurality of unit operations is/are performed); and

(b) cause rendering of a graph-based visualization of the particular manufacturing process via the manufacturing management GUI, wherein the graph- based visualization comprises a plurality of interactive nodes [e.g., graphical icons, such as (e.g., color-coded) inter-connected circular icons], each interactive node of the plurality of interactive nodes representing an individual datapoint corresponding to a particular action that is performed in one of the plurality of unit operations and/or a particular set of information that is collected for a particular one of the plurality the unit operation (e.g., information collected before, during, and/or after the particular unit operation).

69. A system for facilitating experimental process design and data collection for manufacturing production processes via an interactive GUI, the system comprising: a processor of a computing device; and memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:

(a) receive and/or access manufacturing process data corresponding to a particular manufacturing process and representing actions (e.g., unit operations in the particular manufacturing process) performed and/or information collected during the particular manufacturing process; and (b) cause graphical rendering of one or more interactive panels representing the actions and/or information collected during the manufacturing processes, the one or more interactive sub-panels comprising one or more (e.g., up to all) of the following:

(i) a real-time data display panel comprising graphical rendering of data obtained from and/or input to one or more connected devices used (e.g., to perform unit operations and/or collect measurements) during the particular manufacturing process;

(ii) a process design display panel comprising a graphical rendering of one or more unit operations performed during the manufacturing processes (e.g., as linked tiles);

(iii) a data input and calculations panel comprising a graphical rendering of a plurality of fields (e.g., textual input boxes) for input of raw data and corresponding calculations; and

(iv) a material preparation and data calculations panel comprising a graphical rendering of a plurality of input fields and/or output calculations corresponding to material preparation inputs and calculations.