Automated Optimisation of Discrete and Continuous Parameters for Manufacture of Pharmaceuticals

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