WO2012151499A2 - A system for designating, displaying and selecting types of process parameters and product outcome parameters - Google Patents

A system for designating, displaying and selecting types of process parameters and product outcome parameters Download PDF

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Publication number
WO2012151499A2
WO2012151499A2 PCT/US2012/036545 US2012036545W WO2012151499A2 WO 2012151499 A2 WO2012151499 A2 WO 2012151499A2 US 2012036545 W US2012036545 W US 2012036545W WO 2012151499 A2 WO2012151499 A2 WO 2012151499A2
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WO
WIPO (PCT)
Prior art keywords
data
parameters
process parameters
parameter
present
Prior art date
Application number
PCT/US2012/036545
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English (en)
French (fr)
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WO2012151499A3 (en
Inventor
Justin Neway
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Aegis Analytical Corporation
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by Aegis Analytical Corporation filed Critical Aegis Analytical Corporation
Priority to EP12779719.9A priority Critical patent/EP2704682A4/en
Priority to CA2835196A priority patent/CA2835196C/en
Priority to JP2014509480A priority patent/JP2014517962A/ja
Priority to KR1020137032400A priority patent/KR101904864B1/ko
Priority claimed from US13/464,199 external-priority patent/US9275367B2/en
Publication of WO2012151499A2 publication Critical patent/WO2012151499A2/en
Publication of WO2012151499A3 publication Critical patent/WO2012151499A3/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0633—Workflow analysis

Definitions

  • FIG. 4 is a cause-and-effect matrix for part of the manufacturing process of FIG. 2.
  • FIG. 5 is a screenshot of a Universe Properties window of a process intelligence software platform used to analyze the manufacturing process of FIG. 2 according to one embodiment of the present invention.
  • FIG. 9 is a screenshot of a user storing study results related to specifications for a pharmaceutical product for the Chemistry, Manufacturing and Control (CMC) studies for the pharmaceutical product of the manufacturing process of FIG. 2 in a window of a process intelligence software platform according to one embodiment of the present invention.
  • CMC Chemistry, Manufacturing and Control
  • critical attribute refers to a material attribute for an input material for a process that has a risk assessment score that is above a particular threshold that is determined based on prior experience or scientific judgment.
  • a critical attribute is one type of process parameter.
  • critical process parameter refers to a process parameter for one or more processing steps of a process or for a material added to a process that has a risk assessment score that is above a particular threshold that is determined based on prior experience or scientific judgment.
  • data node refers to a node on a hierarchical data structure that represents a restriction on the data leaves beneath the data node in the hierarchical data structure.
  • Inferior data nodes located directly beneath the superior data node in a hierarchical data structure represent the cumulative restrictions of both the superior data node and the inferior data node.
  • the identification code for a data set may be tagged to the data in the data set from which the data for the data set are obtained or may be manually assigned for a data set.
  • An example of manually assigning the identification code for a data set is when there are paper documents providing information such as batch number, lot number or manufacturing ID number for an identification code for a data set, and data from a data set must have this "manually assigned identification code" applied to the data in the data set prior to employing the method of the present invention on the data set.
  • output attribute refers to an attribute for an output.
  • process parameter group refers to a group of process parameters selected by a user in the method of the present invention.
  • a user may set one or more parameter restrictions for one or more of the process parameters in a process parameter group to create an analysis group.
  • an analysis group may include both process parameters and material attributes that are selected based on one or more parameter restrictions.
  • Under data node 310 are data leaf 316 providing access to data for the lot number(s) for the API, data leaf 318 providing access to data for the vendor for the API, data leaf 320 providing access to data for the manufacturing date of the API, data leaf 322 providing access to data for the average particle size of the API, data leaf 324 providing access to data for the degree of agglomeration of the API, data leaf 326 providing access to data for the impurity profile for the API, and data leaf 328 providing access to data from the operation of the milling process.
  • a data node 312 includes data leaves (not shown) providing access to data for excipient materials blending with API during pre-blending step 212.
  • FIG. 5 shows a universe properties window 502 of a data analysis software platform such as Discoverant® that is part of a method for allowing the software platform to display the outcomes of a risk assessment method according to one embodiment of the present invention.
  • Universe properties window 502 includes text boxes 512, 514 and 516 for Process Parameter Process Impact (PI) Rank Settings.
  • Process Parameter PI Rank Settings in the Universe Properties window 502 apply to all process parameters for manufacturing process 202.
  • the value set in text box 512 is the maximum total rank score a process parameter may have.
  • the value set in text box 514 is the minimum total rank score a process parameter may have.
  • One type of software that may be used to implement the methods of the present invention is the Discoverant® enterprise manufacturing intelligence (EMI) platform from Aegis Analytical Corporation.
  • Discoverant® includes features such as: data analysis, dashboarding and reporting, data aggregation, capturing of paper record data, etc.
  • EMI enterprise manufacturing intelligence
  • Many of the features of Discoverant® and techniques that may be used with the present invention are described in U.S. Patent No. 6,725,230 to Ruth et al, entitled “System, method and computer program for assembling process data of multi-database origins using a hierarchical display," issued April 20, 2004, and the entire contents and disclosure of this patent are incorporated herein by reference.

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PCT/US2012/036545 2011-05-05 2012-05-04 A system for designating, displaying and selecting types of process parameters and product outcome parameters WO2012151499A2 (en)

Priority Applications (4)

Application Number Priority Date Filing Date Title
EP12779719.9A EP2704682A4 (en) 2011-05-05 2012-05-04 SYSTEM FOR DESIGNATING, DISPLAYING AND SELECTING TYPES OF PROCESS PARAMETERS AND PRODUCT RESET PARAMETERS
CA2835196A CA2835196C (en) 2011-05-05 2012-05-04 A system for designating, displaying and selecting types of process parameters and product outcome parameters
JP2014509480A JP2014517962A (ja) 2011-05-05 2012-05-04 プロセスパラメータおよび製品成果パラメータのタイプを指定、表示および選択するためのシステム
KR1020137032400A KR101904864B1 (ko) 2011-05-20 2012-05-04 프로세스 파라미터들 및 생산 결과 파라미터들의 타입들을 지정, 디스플레이 및 선택하기 위한 시스템

Applications Claiming Priority (6)

Application Number Priority Date Filing Date Title
US201161482702P 2011-05-05 2011-05-05
US61/482,702 2011-05-05
US201161488202P 2011-05-20 2011-05-20
US61/488,202 2011-05-20
US13/464,199 US9275367B2 (en) 2011-05-05 2012-05-04 System for designating, displaying and selecting types of process parameters and product outcome parameters
US13/464,199 2012-05-04

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WO2012151499A2 true WO2012151499A2 (en) 2012-11-08
WO2012151499A3 WO2012151499A3 (en) 2013-02-21

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CA (1) CA2835196C (ja)
WO (1) WO2012151499A2 (ja)

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CN113597305A (zh) * 2019-03-15 2021-11-02 3M创新有限公司 使用因果模型制造生物药物
US11720070B2 (en) 2019-03-15 2023-08-08 3M Innovative Properties Company Determining causal models for controlling environments

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US11720070B2 (en) 2019-03-15 2023-08-08 3M Innovative Properties Company Determining causal models for controlling environments
US11853018B2 (en) 2019-03-15 2023-12-26 3M Innovative Properties Company Determining causal models for controlling environments
US11927926B2 (en) 2019-03-15 2024-03-12 3M Innovative Properties Company Determining causal models for controlling environments
US11966204B2 (en) 2019-03-15 2024-04-23 3M Innovative Properties Company Determining causal models for controlling environments

Also Published As

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JP2016106302A (ja) 2016-06-16
CA2835196A1 (en) 2012-11-08
CA2835196C (en) 2020-05-05
JP2018085144A (ja) 2018-05-31
WO2012151499A3 (en) 2013-02-21
JP2014517962A (ja) 2014-07-24

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