AI in Drug Discovery and Development

Summary

In pharmacology and drug discovery, computational methods for deriving structure‐activity relationships date back to the 1950s with the foundational work of Corwin Hansch. Success with AI in drug discovery will require some rethinking of the traditional approaches toward tackling problems and retooling of processes for developing drugs. Pharmacological modeling and in silico drug discovery have advanced primarily from incorporating modern computing and statistical techniques to exploit newly available data‐generating technologies and the exponential growth of compound databases. Cheminformatics tools are now critical at the starting point for drug design and screening projects. Structure‐based virtual screening programs and drug design use 3D structures from Protein Data Bank and other sources in small molecule drug discovery. Biotechnology stands as the best model for how technology outside of small molecule chemistry R&D can expand the base of innovation in pharmaceutical research. The pace of advancement in information technology is exponentially greater than in biology and medicine.