Machine Learning Phenotypic De Novo Drug Design

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PROJECT SUMMARY The high rate of failure in CNS drug discovery, in particular of the first-in-class therapeutics with new modes of action, highlights a clear unmet need to improve the success rate in drug discovery for psychiatric disorders. One well-known issue is the poor ability of current bioassays and animal models to predict the efficacy and side- effects of compounds. Another important issue is the lack of clear targets for CNS disorders, which are complex and require polypharmacology. Phenotypic screening platforms are well-suited for drug discovery of compounds in a target-agnostic manner, allowing for the discovery and development of poly pharmacological agents. Suitable proven in vivo phenotypic screens, however, are rare with the exception of PsychoGenics SmartCube® platform, which has been used to screened ~8000 compounds and reference drugs. Compound availability for phenotypic screening, however, restrict discovery to known chemical spaces. Novel machine learning methods are now available to design novel drugs that can be used to poke unexplored chemical spaces. The combination of a machine learning model capturing structure-to-phenotype relationships and a model that can generate novel drug-like compounds promises to deliver a truly novel platform. Our aims therefore are 1) to generate a structure- to-phenotype machine learning model (“PhenCheML”) using our collection of more than 8000 compounds and drugs screened in Psychogenics’ SmartCube® phenotypic in vivo platform, and 2) to combine such model with Collaboration Pharma de novo drug design generative machine learning model MegaSyn®, and generate novel CNS drug-like compounds for testing in vivo. The success of this Phase I SBIR project will result in PhenCheML, a novel phenotypic machine learning-based drug discovery platform that can generate novel chemotypes and predict their therapeutic value. If our Phase I project is successful, we will extend it in a Phase II application through the design and synthesis of novel molecules for test in SmartCube® and validation in second tier assays focusing on psychiatric disorders (depression, anxiety, psychosis, and bipolar disorder). We will also explore the use of the platform for generation of novel compounds with potential therapeutic effects in model systems of psychiatric, neurodevelopmental, and neurodegenerative disease (e.g., Rett, ASD, HD, PD, etc). If successful, this platform will be an innovative and unique drug design method, offered by as fee-for-service or used in drug development by PGI and its partners.