Pharma researchers turn to AI to expedite drug development

If AI algorithms can successfully slash drug development times and increase success ratios, a growing number of patients should have lower drug prices to look forward to.
Jeff Rowe

Regardless of the myriad political debates sparked by the pharmaceutical industry, the fact remains that developing new drugs is expensive.

According to the Tufts Center for the Study of Drug Development, for example, the costs to bring a new drug onto the market was $2.6 billion in 2014, with an average time to market of 12 years.

Not surprisingly, then, pharma researchers are increasingly turning to AI, machine learning and big data for help. For proof, says one tech investment writer, just look at the increased rate of investment and interest from startups.

For example, he says, BenevolentAI “is one startup that attempts to connect the dots from previous pharma studies for drug discovery. Its technology employs AI to analyze and mine biomedical data from previous clinical trials and academic research to assess whether certain compounds could be better used in targeting other diseases. Theoretically, its AI predictive capabilities can design new molecules based on relationships between genes, drugs, diseases, and other data points.”

Other startups tapping big data from patients to identify new targets and pursue drugs R&D through AI include Berg Health, Atomwise, and Insilico Medicine. Big tech companies have also jumped into the race, with Google and China’s Tencent now two of the biggest names in pharmaceuticals AI.

As for Big Pharma itself, the giants are also increasingly turning to AI for help.  

Merck, for example, has been partnered with AI developer Numerate since back in 2012 to develop potential new drugs for cardiovascular diseases using in silico drug design technology algorithms. 

More recently, the writer says, all of the pharmaceuticals giants, including Pfizer, Novartis and Bayer, have actively integrated AI into drug discovery. “However, insiders suggest that most of their initiatives are still at an experimental stage, and more full-scale commitments are required.”

Finally, of all the pharma brands, the writer notes GlaxoSmithKline seems to be most invested in AI,” having partnered with several AI drug discovery startups (including Insilico), while turning over data on two million compounds to the ATOM consortium, a public-private partnership focused on accelerating drug discovery.”