A cross-disciplinary team of researchers have published details of an artificial intelligence (AI) guided robotic platform for flow synthesis of small molecule organic compounds. The paper appeared in the issue of Science.
While small organic molecules are essential for many disciplines including drug discovery, the identification and development of synthetic routes creates a bottleneck due to the need for time-consuming manual tasks and lengthy design-synthesize-test iterations. Despite the availability of laboratory automation, experimental synthesis platforms still require manual configuration by expert chemists.
In this publication, the authors describe the development and use of a platform that combines artificial intelligence-driven synthesis planning, flow chemistry and a robotically controlled experimental platform to minimize the need for human intervention in the synthesis process from ideation through to manufacturing. Synthetic routes are proposed through generalization of millions of published chemical reactions and validated in silico to maximize the likelihood of success. Additional implementation details are determined by expert chemists and recorded in 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.
To execute these syntheses, a robotic arm assembles modular process units (reactors and separators) into a continuous flow path according to the desired process configuration defined in the CRF. The robot also connects reagent lines and computer-controlled pumps to reactor inlets through a fluidic switchboard. When that is completed, the system primes the lines and starts the synthesis. After a specified synthesis time, the system flushes the lines with a cleaning solvent, and the robotic arm disconnects reagent lines and removes process modules to their appropriate storage locations.
This paradigm of flow chemistry development was demonstrated for a suite of 15 medicinally relevant small molecules. In order of increasing complexity, the authors investigated the synthesis of aspirin and secnidazole run back to back; lidocaine and diazepam run back to back to use a common feedstock; (S)-warfarin and safinamide to demonstrate the planning program’s stereochemical awareness; and two compound libraries: a family of five ACE inhibitors including quinapril and a family of four nonsteroidal anti-inflammatory drugs including celecoxib. These targets required a total of eight particular retrosynthetic routes and nine specific process configurations.
"One of the major challenges in automating small molecule synthesis is the diversity of organic reactions and the difficulty in finding compatible reaction conditions to support multistep synthesis. Additionally, creating a system capable of supporting the range of reaction conditions in terms of temperatures, pressures and chemical compatibilities poses a serious engineering challenge," said a co-first author on the Science publication.
Organic compound synthesis using AI-guided robotics platform
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