By Mark Eller
Drug development is a complex, highly regulated practice that relies, most importantly, on experiments and their results.
The initial discovery step relies on human insight to generate hypotheses worth testing in the first experiments. Insights come through knowledge, experience, patience and instinct. Best practices are handed down from researcher to researcher, which in turn helps companies build and refine their hypotheses and grow their pipelines. That has been the traditional path to drug discovery. Another is that computers and artificial intelligence (AI) can replace this traditional model and expedite the entire process. The dichotomy between these two approaches is very real.