A robotic platform for flow synthesis of organic compounds informed by AI planning

The synthesis of complex organic molecules requires several stages, from ideation to execution, that require time and effort investment from expert chemists. Here, we report a step toward a paradigm of chemical synthesis that relieves chemists from routine tasks, combining artificial intelligence-dr...

Full description

Saved in:
Bibliographic Details
Published in:Science (American Association for the Advancement of Science) Vol. 365; no. 6453
Main Authors: Coley, Connor W, Thomas, 3rd, Dale A, Lummiss, Justin A M, Jaworski, Jonathan N, Breen, Christopher P, Schultz, Victor, Hart, Travis, Fishman, Joshua S, Rogers, Luke, Gao, Hanyu, Hicklin, Robert W, Plehiers, Pieter P, Byington, Joshua, Piotti, John S, Green, William H, Hart, A John, Jamison, Timothy F, Jensen, Klavs F
Format: Journal Article
Language:English
Published: United States The American Association for the Advancement of Science 09-08-2019
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The synthesis of complex organic molecules requires several stages, from ideation to execution, that require time and effort investment from expert chemists. Here, we report a step toward a paradigm of chemical synthesis that relieves chemists from routine tasks, combining artificial intelligence-driven synthesis planning and a robotically controlled experimental platform. Synthetic routes are proposed through generalization of millions of published chemical reactions and validated in silico to maximize their likelihood of success. Additional implementation details are determined by expert chemists and recorded in reusable recipe files, which are executed by a modular continuous-flow platform that is automatically reconfigured by a robotic arm to set up the required unit operations and carry out the reaction. This strategy for computer-augmented chemical synthesis is demonstrated for 15 drug or drug-like substances.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0036-8075
1095-9203
DOI:10.1126/science.aax1566