ChemistryNature Chemistry
Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning
D. F. Nippa, K. Atz, et al.
Discover how a groundbreaking platform that integrates geometric deep learning with high-throughput reaction screening revolutionizes late-stage functionalization in drug development. This innovative research, conducted by a team including David F. Nippa and Kenneth Atz, reveals powerful strategies for optimizing drug candidates through predictive modeling and enhanced reaction yields.
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