Recent innovations in automated chemical synthesis technologies, high-throughput biological screening, automation engineering, and machine learning/artificial intelligence (AI) indicate that now is the time to converge these technologies and advance our understanding of the relationship between chemical and biological space. While symbiosis of the above technologies has tremendous potential to advance drug development, with the input of the scientific community, funders, publishers and other interested stakeholders, NCATS has identified a number of challenges that surround the application of machine learning to drug development. These challenges include but are not limited to lack of standardization in chemistry; insufficient quality, variety and quantity of data in databases; lack of user-friendly electronic laboratory notebooks to provide better quality and quantity of day-to-day data and be accessible for machine learning; and limitations of biological assays that are currently used to identify and validate promising drug candidates. To address some of these issues and help catalyse the discovery and development of novel, safe, and effective treatments, while at the same time making the process faster and more cost-effective, NCATS is supporting the development of A Specialized Platform for Innovative Research Exploration (ASPIRE). ASPIRE aims to ignite development of innovative algorithms to predict and synthesize novel structures capable of interacting with specific targets; enable small-scale synthesis of the predicted molecules; and incorporate in-line, rapid biological testing of the molecules. If successful, this concerted and collaborative effort will revolutionize drug discovery and development. ASPIRE’s ultimate goal is to bring the promise of science to those in need of new or improved safe and effective treatments.

NCATS ASPIRE: Synergizing engineering, synthetic chemistry, machine learning/AI, and biology to advance drug development

2019 Fall National Meeting

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