Machine learning-driven protein engineering: a case study in computational drug discovery.

Research and development in drug discovery will need to find significant efficiency gains if the industry is to continue generating novel drugs. There is great expectation for machine learning (ML) to provide this boost in R&D productivity, but to harness the full potential of ML, the generation of new, high-quality datasets will be necessary. Here, the authors present a platform that combines high-throughput display and selection data generation with ML.