How AI Could Speed Drug Discovery

Technological advances in recent years have made it easier to capture and store reams of digital patient data. This has resulted in rich troves of genomic data, health records, medical imaging and other patient information that AI platforms can mine to help to develop drugs faster and with greater chance of success in the early stages of creation. Morgan Stanley Research biotechnology analysts Matthew Harrison and Vikram Purohit estimate that "a 20% to 40% reduction in costs for preclinical development across a subset of U.S. biotech companies could generate the cost savings needed to fund the successful development of four to eight novel molecules." This would represent as much as a 15% increase of approved therapies over the total number of novel drug approvals in 2021, demonstrating the potential for biotechs to generate new revenue while helping more patients. The pairing of AI and big data could help patients in other ways.