The basic steps involved in developing a new drug from scratch haven’t changed much. It could be a few years yet before the first drugs designed with the help of AI hit the market, but the technology is set to shake up the pharma industry, from the earliest stages of drug design to the final approval process. “But the ultimate validation needs to be done in the lab.” Still, AI is already changing how drugs are being made. It’s already doing a lot of the steps that we used to do by hand,” says Luisa Salter-Cid, chief scientific officer at Pioneering Medicines, part of the startup incubator Flagship Pioneering in Cambridge, Massachusetts. There are a lot of AI companies making claims they can’t back up, says Prakash: “If somebody tells you they can perfectly predict which drug molecule can get through the gut or not get broken up by the liver, things like that, they probably also have land to sell you on Mars.”Īnd the technology is not a panacea: experiments on cells and tissues in the lab and tests in humans-the slowest and most expensive parts of the development process-cannot be cut out entirely. Yet it is still early days for AI drug discovery. “We’re going to see huge transformation in this industry over the next five years.” We’re seeing this uptick in activity and investment because increasing automation in the pharmaceutical industry has started to produce enough chemical and biological data to train good machine-learning models, explains Sean McClain, founder and CEO of Absci, a firm based in Vancouver, Washington, that uses AI to search through billions of potential drug designs. “If somebody tells you they can perfectly predict which drug molecule can get through the gut … they probably also have land to sell you on Mars.” Adityo Prakash, CEO of Verseon All told, around two dozen drugs (and counting) that were developed with the assistance of AI are now in or entering clinical trials. Last year Exscientia opened a new research center in Vienna in February, Insilico Medicine, a drug discovery firm based in Hong Kong, opened a large new lab in Abu Dhabi. Now, new labs are being built around the world. By predicting how potential drugs might behave in the body and discarding dead-end compounds before they leave the computer, machine-learning models can cut down on the need for painstaking lab work.Īnd there is always a need for new drugs, says Adityo Prakash, CEO of the California-based drug company Verseon: “There are still too many diseases we can’t treat or can only treat with three-mile-long lists of side effects.” The vision is to use AI to make drug discovery faster and cheaper. Today, on average, it takes more than 10 years and billions of dollars to develop a new drug. There are now hundreds of startups exploring the use of machine learning in the pharmaceutical industry, says Nathan Benaich at Air Street Capital, a VC firm that invests in biotech and life sciences companies: “Early signs were exciting enough to attract big money.” “If we were using a traditional approach, we couldn’t have scaled this fast,” Hopkins says.Įxscientia isn’t alone. The company is on the way to submitting two more. Since 2021, two drugs that Exscientia developed (or co-developed with other pharma companies) have started the process. The first drugs designed with the help of AI are now in clinical trials, the rigorous tests done on human volunteers to see if a treatment is safe-and really works-before regulators clear them for widespread use. This could in turn yield even more options to sift through when looking for a match. In addition to pairing patients up with existing drugs, Exscientia is using machine learning to design new ones. The company is set on overhauling the entire drug development pipeline. Selecting the right drug is just half the problem that Exscientia wants to solve.
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