Insilico's AI networks generate custom lead compounds for fibrosis in less than 50 days

In the gold rush to bring artificial intelligence to the healthcare and biopharma industries, AI has long been pitched as a way to accelerate the pace of drug development and discovery. Sometimes vaguely and sometimes not, many companies have claimed their code can help early research get done quicker, deeper and cheaper. Now, Insilico Medicine may have hit pay dirt, demonstrating in a paper published in Nature Biotechnology that its computer networks could potentially shave years off of traditional hit-to-lead timelines. Over 21 days, the startup and its partners used its AI programs to conceptualize and generate 30,000 novel small molecules that may work against fibrosis. Within 25 more days, they had screened out and synthesized the six most promising compounds, tested them in vitro for selectivity and metabolic stability and had the lead candidate go on to show favorable activity in live mouse models.