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.

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.

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Hepsin is a membrane-anchored serine protease whose role in hepatocyte growth factor (HGF) signaling and epithelial integrity makes it a target of therapeutic interest in carcinogenesis and metastasis. Using an integrated design, synthesis, and screening platform, we were able to rapidly develop potent and selective inhibitors of hepsin. In progressing from the initial hit 7 to compound 53, the IC value against hepsin was improved from ∼1 μM to 22 nM, and the selectivity over urokinase-type plasminogen activator (uPA) was increased from 30-fold to >6000-fold. Subsequent in vitro ADMET profiling and cellular studies confirmed that the leading compounds are useful tools for interrogating the role of hepsin in breast tumorigenesis.

A prototype sphingomyelin stationary phase for Immobilized Artificial Membrane (IAM) chromatography was synthesized by an ultra-short, solid-phase inspired methodology, in which an oxidative release monitoring strategy played a vital role. Evaluated in a proof-of-concept model for blood-brain barrier passage, partial least squares regression demonstrated its potential as an in vitro prediction tool.