WO2024246672A1 - Method and system for self-driving labs - Google Patents

Method and system for self-driving labs Download PDF

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Publication number
WO2024246672A1
WO2024246672A1 PCT/IB2024/054922 IB2024054922W WO2024246672A1 WO 2024246672 A1 WO2024246672 A1 WO 2024246672A1 IB 2024054922 W IB2024054922 W IB 2024054922W WO 2024246672 A1 WO2024246672 A1 WO 2024246672A1
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WO
WIPO (PCT)
Prior art keywords
ncc
platform
module
robotic equipment
self
Prior art date
Application number
PCT/IB2024/054922
Other languages
French (fr)
Inventor
Loïc Michel ROCH
Sébastien Martial CRÉOFF
Alain FOULON
Daniel Mauricio Pacheco GUTIERREZ
Original Assignee
Atinary Technologies Sàrl
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 Atinary Technologies Sàrl filed Critical Atinary Technologies Sàrl
Publication of WO2024246672A1 publication Critical patent/WO2024246672A1/en

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N35/00—Automatic analysis not limited to methods or materials provided for in any single one of groups G01N1/00 - G01N33/00; Handling materials therefor
    • G01N35/00584—Control arrangements for automatic analysers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N35/00—Automatic analysis not limited to methods or materials provided for in any single one of groups G01N1/00 - G01N33/00; Handling materials therefor
    • G01N35/0099—Automatic analysis not limited to methods or materials provided for in any single one of groups G01N1/00 - G01N33/00; Handling materials therefor comprising robots or similar manipulators
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/40—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis

Definitions

  • the present invention generally relates to autonomous or self-driving laboratories combining one or several automated robotic equipment(s) with artificial intelligence and machine learning (AI/ML) algorithms.
  • AI/ML artificial intelligence and machine learning
  • ChemOS an orchestration software to democratize autonomous discovery (ChemRxiv, March 7, 2018)
  • the present invention provides an optimized method and system for using and enabling a selfdriving laboratory that includes at least one robotic equipment.
  • the method according to the invention comprises the remote connection of AI/ML -that serve as experiment planners- to the automated robotic equipment, via a network, and can optimize the experimental conditions or parameters in full autonomy.
  • the invention can be used in a wide variety of applications, such as experiments in research and development (R&D), process development and process scale-up, formulation, synthesis, catalysis across industries, including in chemistry, materials science, pharma, biotechnology, agrotechnology, fragrances, food, and energy.
  • the method according to the invention comprises the following steps: a) Users connect remotely to a No-Code Cloud (NCC) platform from their computers, smartphones or tablets.
  • NCC No-Code Cloud
  • the connection to the NCC may be established using a Graphical User Interface (GUI), an Application Programming Interface (API) or a Software Development Kit (SDK).
  • GUI Graphical User Interface
  • API Application Programming Interface
  • SDK Software Development Kit
  • Users define their experiments, including input parameters and measurements or objectives.
  • a NCC platform that communicates with a module of AI/ML algorithms, named “experiment planners”, and preferably with a database(s) module to control automated robotic equipment(s), to drive, orchestrate and execute operations, such as experiments, in full autonomy.
  • the NCC platform acts as a workflow manager and as a queuing system.
  • the experiment planners module may advantageously include trial-and-error methods, design of experiment methods, grid search methods, AI/ML algorithms.
  • the database(s) module comprises data from users that are automatically updated as each experiment is being optimized by the experiment planners module.
  • the network allows the transfer of experimental conditions from computing device(s) to control the robotic equipment(s), including for instance RESTful application programming interfaces (API), software development kits (SDKs) and file transfer protocols.
  • API application programming interfaces
  • SDKs software development kits
  • the network automatically translates the set of conditions from experiment planners to the format required by the control of the robotic equipment(s).
  • One or several equipment(s) may be simultaneously controlled.
  • the system according to the invention may be configured in different manners.
  • a NCC platform communicates with the “experiment planners” module to control at least one automated robotic equipment, to drive, orchestrate and execute operations, such as experiments, in full autonomy.
  • This configuration is identical to configuration 1 but with the addition of a module including at least one database to digitize users' experimental result(s).
  • This configuration is identical to configuration 2 but with the addition of a data processing module to interpret experimental results.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Analytical Chemistry (AREA)
  • Chemical & Material Sciences (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Strategic Management (AREA)
  • Health & Medical Sciences (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Biochemistry (AREA)
  • Educational Administration (AREA)
  • Game Theory and Decision Science (AREA)
  • Development Economics (AREA)
  • Robotics (AREA)
  • Marketing (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • General Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • General Factory Administration (AREA)

Abstract

Method for enabling and optimizing the use of a self-driving laboratory comprising a No-Code Cloud (NCC) platform and an automated robotic equipment; wherein said NCC platform communicates at least with a module of AI/ML algorithms to control said automated robotic equipment, to drive, orchestrate and execute operations, such as experiments, in full autonomy. The invention also relates to a system for self-driving laboratories comprising a No-Code Cloud (NCC) platform, a module of AI/ML algorithms and at least one robotic equipment; said NCC platform and experiment planners module being configured to control said robotic equipment.

Description

Method and system for self-driving labs
Field of invention
The present invention generally relates to autonomous or self-driving laboratories combining one or several automated robotic equipment(s) with artificial intelligence and machine learning (AI/ML) algorithms.
Prior art
Self-driving laboratories using Al algorithms are disclosed in the following references:
- ChemOS: an orchestration software to democratize autonomous discovery (ChemRxiv, March 7, 2018)
- ChemOS: Orchestrating autonomous experimentation (Science Robotics, June 20, 2018)
Description of the invention
The present invention provides an optimized method and system for using and enabling a selfdriving laboratory that includes at least one robotic equipment.
The method according to the invention comprises the remote connection of AI/ML -that serve as experiment planners- to the automated robotic equipment, via a network, and can optimize the experimental conditions or parameters in full autonomy.
The invention can be used in a wide variety of applications, such as experiments in research and development (R&D), process development and process scale-up, formulation, synthesis, catalysis across industries, including in chemistry, materials science, pharma, biotechnology, agrotechnology, fragrances, food, and energy. The method according to the invention comprises the following steps: a) Users connect remotely to a No-Code Cloud (NCC) platform from their computers, smartphones or tablets. The connection to the NCC may be established using a Graphical User Interface (GUI), an Application Programming Interface (API) or a Software Development Kit (SDK). b) Users define their experiments, including input parameters and measurements or objectives. c) Users select the AI/ML algorithm (experiment planner) that will suggest experimental conditions for the first iteration of experiments. d) Users define the means of communication to the automated or robotic equipment present in their laboratories. e) Users start experiments. f) The experiment planner suggests experimental conditions, which are sent automatically to the device(s) controlling automated or robotic equipment through the network. g) The results of the experiment, or measurements, are automatically collected by computing device, stored in digital databases in the NCC platform and used to retrain AI/ML algorithms so that these suggest the new values for each parameter, that is, the best set of experimental conditions to use in the next iteration of experiments, and submits these instructions automatically to the control device.
The invention provides several advantages and original features with respect to the prior art, in particular:
- A NCC platform that communicates with a module of AI/ML algorithms, named “experiment planners”, and preferably with a database(s) module to control automated robotic equipment(s), to drive, orchestrate and execute operations, such as experiments, in full autonomy.
The NCC platform acts as a workflow manager and as a queuing system.
The experiment planners module may advantageously include trial-and-error methods, design of experiment methods, grid search methods, AI/ML algorithms. The database(s) module comprises data from users that are automatically updated as each experiment is being optimized by the experiment planners module.
The network allows the transfer of experimental conditions from computing device(s) to control the robotic equipment(s), including for instance RESTful application programming interfaces (API), software development kits (SDKs) and file transfer protocols.
The network automatically translates the set of conditions from experiment planners to the format required by the control of the robotic equipment(s).
One or several equipment(s) may be simultaneously controlled.
The system according to the invention may be configured in different manners.
Some configurations are briefly presented hereafter.
Configuration 1 (figure 1)
A NCC platform communicates with the “experiment planners” module to control at least one automated robotic equipment, to drive, orchestrate and execute operations, such as experiments, in full autonomy.
Configuration 2 (figure 2)
This configuration is identical to configuration 1 but with the addition of a module including at least one database to digitize users' experimental result(s).
Configuration 3 (figure 3)
This configuration is identical to configuration 2 but with the addition of a data processing module to interpret experimental results.

Claims

Claims
1. Method for enabling and optimizing the use of a self-driving laboratory comprising a No-Code Cloud (NCC) platform and an automated robotic equipment; wherein said NCC platform communicates at least with a module of AI/ML algorithms to control said automated robotic equipment, to drive, orchestrate and execute operations, such as experiments, in full autonomy.
2. Method according to claim 1 wherein said NCC platform also communicates with a database(s) module to digitize users’ experimental results.
3. Method according to claim 1 or 2 wherein said NCC platform also communicates with a data processing module to interpret experimental results.
4. System for self-driving laboratories comprising a No-Code Cloud (NCC) platform, a module of AI/ML algorithms and at least one robotic equipment; said NCC platform and experiment planners module being configured to control said robotic equipment.
5. System according to claim 4 furthermore comprising a database(s) module.
6. System according to claim 4 or 5 furthermore comprising a data processing module.
PCT/IB2024/054922 2023-05-26 2024-05-21 Method and system for self-driving labs WO2024246672A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
IB2023055408 2023-05-26
IBPCT/IB2023/055408 2023-05-26

Publications (1)

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WO2024246672A1 true WO2024246672A1 (en) 2024-12-05

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090138415A1 (en) * 2007-11-02 2009-05-28 James Justin Lancaster Automated research systems and methods for researching systems
US20150242395A1 (en) * 2014-02-24 2015-08-27 Transcriptic, Inc. Systems and methods for equipment sharing
US20220040862A1 (en) * 2020-08-04 2022-02-10 Artificial, Inc. Protocol simulation in a virtualized robotic lab environment

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090138415A1 (en) * 2007-11-02 2009-05-28 James Justin Lancaster Automated research systems and methods for researching systems
US20150242395A1 (en) * 2014-02-24 2015-08-27 Transcriptic, Inc. Systems and methods for equipment sharing
US20220040862A1 (en) * 2020-08-04 2022-02-10 Artificial, Inc. Protocol simulation in a virtualized robotic lab environment

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
"ChemOS: an orchestration software to democratize autonomous discovery", CHEMRXIV, 7 March 2018 (2018-03-07)
"ChemOS: Orchestrating autonomous experimentation", SCIENCE ROBOTICS, 20 June 2018 (2018-06-20)

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