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Finite Element Modelling of a Cellular Electric Microenvironment

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Routescore: Punching the Ticket to More Efficient Materials Development.

Martin Seifrid^1,2, Riley J Hickman^1,2, Andrés Aguilar-Granda^1,2

¹Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada.

ACS Central Science

|February 2, 2022

Summary

Self-driving laboratories accelerate science by integrating automated and manual synthesis. A new protocol, RouteScore, quantifies synthetic costs, optimizing chemical exploration for pharmaceuticals and materials.

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Area of Science:

Chemistry
Computer Science
Materials Science

Background:

Automated experimentation platforms, or self-driving laboratories, are crucial for accelerating scientific discovery.
Automated synthesis is a significant bottleneck, limiting the chemical space accessible to these platforms.
Integrating manual synthesis expands accessible chemical diversity.

Purpose of the Study:

To introduce a protocol, RouteScore, for quantifying the cost of combined synthetic routes.
To optimize the use of both automated and manual synthesis capabilities.
To demonstrate the protocol's utility in structure-oriented and property-oriented optimization problems.

Main Methods:

Developed the RouteScore protocol to estimate synthetic costs.
Applied RouteScore to determine the most efficient synthetic route for a pharmaceutical.
Simulated a self-driving laboratory using RouteScore to identify synthesizable organic laser molecules.

Main Results:

RouteScore effectively quantifies the cost of combined synthetic routes.
The protocol successfully optimized synthetic routes for a pharmaceutical.
Identified easily synthesizable organic laser molecules from a large chemical space using RouteScore.

Conclusions:

RouteScore provides a powerful and flexible approach for mixed synthetic planning and optimization.
The protocol enables efficient downselection of promising candidates from vast chemical spaces.
This method significantly enhances the capabilities of self-driving laboratories.