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

作者：Connor W. Coley, Dale A. Thomas, Justin A. M. Lummiss, Jonathan N. Jaworski, C. Breen, Victor Schultz, Travis Hart, Joshua Fishman, Luke Rogers, Hanyu Gao, Robert W. Hicklin, Pieter Plehiers, Joshua Byington, John S. Piotti, William H. Green, A. John Hart, Timothy F. Jamison, Klavs F. Jensen · 发表于：Science · 年份：2019 · DOI：10.1126/science.aax1566 · 被引用次数：1132 · 研究领域：Innovative Microfluidic and Catalytic Techniques Innovation、Machine Learning in Materials Science、Chemical Synthesis and Analysis

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.