Automated Synthesis Workflow for Dynamic Compound Screening
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Solution Overview
Problem
Existing methods for drug discovery are inefficient and inefficient, with a focus on existing technologies struggling to automate complex workflows and requiring manual intervention and inefficient screening of compounds.
Innovation Solution
Implementing a workflow using automated reaction devices, machine learning models, and workflows to automate compound development, synthesis, and screening, enabling dynamic performance of molecular reactions and removing the need for manual customization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual lab processes are used for drug discovery, then flexibility and adaptability are maintained, but productivity and efficiency are significantly reduced
Solution Approach 1:
The system enables self-service automation through autonomous worklist generation and execution. The automated platform performs compound synthesis and screening without continuous manual intervention, with the system automatically generating worklists, executing reactions, and producing outputs for the next cycle, thereby dramatically improving productivity while maintaining adaptability through programmable control.
2Adaptability or versatility
If traditional fixed-input worklists are used for automation, then device complexity is reduced, but adaptability and versatility for complex workflows are limited
Solution Approach 1:
The system implements dynamic worklist configuration that allows parameters and steps to be adjusted based on real-time experimental conditions and requirements. The automated platform can dynamically modify reaction parameters, reagent amounts, and procedural steps without requiring complete reprogramming, enabling flexible adaptation to complex workflows while managing system complexity through modular design.
Solution Approach 2:
The system utilizes parameter changes to achieve workflow adaptability. By modifying worklist parameters such as reaction conditions, reagent concentrations, and procedural timing, the system can accommodate different experimental scenarios and complex multi-instrument workflows without increasing fundamental system complexity, allowing the same automated platform to handle diverse drug discovery tasks.
3Productivity
If manual customization of worklists is performed for each design-make-test cycle, then measurement precision and control are maintained, but loss of time and productivity are increased
Solution Approach 1:
The system performs preliminary action by pre-configuring standardized worklist templates and protocols for common drug discovery workflows. These pre-established templates contain validated reaction conditions and procedural steps that can be directly applied or minimally modified for new experiments, eliminating the need for time-consuming manual customization for each design-make-test cycle while maintaining precision through proven protocols.
Solution Approach 2:
The system utilizes copying by replicating successful worklist configurations across multiple experiments. Once a worklist is optimized for a particular reaction type or screening assay, it can be copied and reused for similar experiments, significantly reducing the time required for worklist preparation while maintaining consistent quality and precision across all iterations of the design-make-test cycle.
Data Source
AI summary
Systems and methods for implementing a workflow are provided. A workflow is obtained including a plurality of target compounds and a plurality of synthesis tasks collectively configured to synthesize the plurality of target compounds. Each synthesis task includes a corresponding specification including an identification of respective solvent, an amount of a reactant, an address of a well in a multi-well plate, a reaction duration, a reaction temperature, and a reaction volume. A respective subset of the plurality of synthesis tasks is performed including reacting the plurality of reactants in the plurality of wells in accordance with the corresponding specification of at least the respective subset of the plurality of synthesis tasks. A data set associated with a physical property of a liquid in each well specified by the corresponding specification is informed. The performing and obtaining are repeated until each synthesis task has been performed. An amount of each target compound that was synthesized is determined and used to amend the corresponding specification of each synthesis task in the plurality of synthesis tasks.