Automated Optimisation of Discrete and Continuous Parameters for Manufacture of Pharmaceuticals

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Automation has been applied to the optimization of chemical synthesis in flow reactors using algorithms to automatically explore and fine-tune reaction conditions. The Bourne lab (Leeds, UK) has developed a system which self-optimizes continuous variables (e.g. temperature, reagent equivalents, residence time) and has successfully transferred this technology to industrial partners. This Bourne lab-Pfizer collaboration aims to explore liquid handling robotics and mathematical techniques to extend the scope to non-continuous variables such as reagent, catalyst and solvent choice, thus accelerating the screening and optimization of flow-amenable chemistries, as well as investigating reductions in material usage. Objectives: Development of workflows, instrumentation, control software and computational protocols to allow non-continuous variable self-optimization using liquid handling robotics Development of computational protocols to allow non-continuous variable self-optimization using mathematical techniques such as chemical descriptors Studies into minimization of material usage in self-optimization workflows