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Desai B.,Cyclofluidic Ltd. | Dixon K.,Cyclofluidic Ltd. | Farrant E.,Cyclofluidic Ltd. | Feng Q.,Cyclofluidic Ltd. | And 10 more authors.
Journal of Medicinal Chemistry | Year: 2013

Drug discovery faces economic and scientific imperatives to deliver lead molecules rapidly and efficiently. Using traditional paradigms the molecular design, synthesis, and screening loops enforce a significant time delay leading to inefficient use of data in the iterative molecular design process. Here, we report the application of a flow technology platform integrating the key elements of structure-activity relationship (SAR) generation to the discovery of novel Abl kinase inhibitors. The platform utilizes flow chemistry for rapid in-line synthesis, automated purification, and analysis coupled with bioassay. The combination of activity prediction using Random-Forest regression with chemical space sampling algorithms allows the construction of an activity model that refines itself after every iteration of synthesis and biological result. Within just 21 compounds, the automated process identified a novel template and hinge binding motif with pIC50 > 8 against Abl kinase - both wild type and clinically relevant mutants. Integrated microfluidic synthesis and screening coupled with machine learning design have the potential to greatly reduce the time and cost of drug discovery within the hit-to-lead and lead optimization phases. © 2013 American Chemical Society. Source

Czechtizky W.,Sanofi S.A. | Dedio J.,Sanofi S.A. | Desai B.,Cyclofluidic Ltd. | Dixon K.,Cyclofluidic Ltd. | And 9 more authors.
ACS Medicinal Chemistry Letters | Year: 2013

A novel integrated discovery platform has been used to synthesize and biologically assay a series of xanthine-derived dipeptidyl peptidase 4 (DPP4) antagonists. Design, synthesis, purification, quantitation, dilution, and bioassay have all been fully integrated to allow continuous automated operation. The system has been validated against a set of known DPP4 inhibitors and shown to give excellent correlation between traditional medicinal chemistry generated biological data and platform data. Each iterative loop of synthesis through biological assay took two hours in total, demonstrating rapid iterative structure-activity relationship generation. © 2013 American Chemical Society. Source

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