TechRepublic's Karen Roby talked with Dr. Krishnan Nandabalan of InveniAI about the ways artificial intelligence (AI) is helping companies discover new medications. The following is an edited transcript of their interview. Krishnan Nandabalan: AI could be considered as a force multiplier. If you look at the amount of data that the world has been gathering for the past few years, it kind of doubles every two years now, and if you take the medical field, especially on a daily basis, more than 5,000 publications are being added. It's humanly impossible to actually keep track of all of these things, and seeing which of them are relevant to you in your specific area of investigational research, and what is not.

The need for new medications is higher than ever, but so is the cost and time to bring them to market. Developing a new drug can cost billions and take as long as 14 years, according to the U.S. Food and Drug Administration. Yet with all that effort, only 8 percent of drugs make it to market, the FDA said. "We need to make smarter decisions about which potential medicines we develop and test," said Abraham Heifets, co-founder of San Francisco-based startup Atomwise. The six-year-old company, a member of our Inception startup incubator program, is working to make that happen by using GPU-accelerated deep learning to predict which molecules are most likely to lead to treatments.