How AI Is Aiming at the Bad Math of Drug Development 

A new drug typically takes more than a decade to develop, at a cost of almost $3 billion. That’s because about 90% of experimental medicines fail during the various stages of chemical engineering, or during animal or human trials. So drugmakers and investors are spending billions of dollars to turbocharge the search for new treatments using artificial intelligence. Scientists are looking to discover breakthrough medicines by rapidly identifying new compounds and modeling complex mechanisms in the body, and by automating what used to be manual processes. So far only a trickle of treatments created with the much-hyped technology have reached the testing stage.

There are about 10,000 diseases that affect humans (most of them are rare), and the majority lack an effective treatment. Often scientists can only guess at the mechanism that’s causing an illness, let alone identify a treatment or cure. There’s conjecture, too, in deciding which therapy to try among many trillions of possible medicines that could be chemically synthesized or made with biologics, which are generally produced with genetically engineered cells. That makes for a process marked by trial and error.