The recent drug programs offered a straightforward promise: By acquiring extensive datasets, machine learning would address enduring challenges in the discovery, development, and testing of new pharmaceuticals. However, many of these initiatives have encountered significant obstacles recently.
In recent years, individuals who have integrated computer science with biology have found it relatively easy to secure funding to transition their innovations into the commercial sector. The proposition was straightforward: access extensive datasets, and machine learning would address longstanding challenges in the discovery, development, and testing of new pharmaceuticals.