Even health AI can be risky but innovation must win

livemint.com:

One of my favourite podcasts is ‘Radiolab’, a show that, by its own description, asks deep questions and uses investigative journalism to get answers. In an episode last year, it told the story of an artificial intelligence tool called MegaSyn that, though it had been developed to find a cure for disease, ended up being used in far more sinister ways. Drug discovery has always been a tedious and time-consuming affair.

Scientists need to first identify the biological target (the specific protein or gene that is involved in the disease) and confirm what its role is. They then need to find chemical compounds that will interact with the target in such a manner that it ends up curing the disease. This is a process of trial and error, and while we’ve become better at figuring it out over the years, even today researchers have little choice but to cycle through vast libraries of potential compounds in order to figure out which molecule would work best—a process that can often take years.

It is here that recent advances in computational technology have begun to make a significant difference. Today, we can use computer simulations to identify, with a high degree of accuracy, potential drug candidates—allowing us to prioritize a small sub-set of compounds for further testing in a laboratory. This has helped overcome some of the delays that have plagued the process in the past.

While shortlisting possible candidates, we are, however, constrained by our current knowledge. As a result, the list of compounds from which we get to choose is finite. What if the cure we need involves a molecule we have not yet discovered? This is the problem that Collaborations Pharmaceuticals set out to solve using MegaSyn.