WILMINGTON — Incyte Corporation is now working with artificial intelligence to ideally speed up the drug discovery process, starting with two undisclosed drug targets to start with.
Earlier this year,
Incyte inked a deal with
Genesis Therapeutics to use the biotech company’s AI platform to develop small molecule medicines. Genesis was paid $30 million upfront, but it could stand to earn another $295 million per target for each development, regulatory and commercial milestone hit.
“AI has the potential to redefine how we discover small molecule medicines, and our team is at the forefront of this revolution,” Genesis CEO Evan Feinberg said in a press release at the time the deal was signed.
In biotech, companies have promised to use AI and machine learning to make better drugs faster for at least a decade. Incyte President and Head of Research Development Pablo Cagnoni said the reality is that there’s still a disconnect between machine learning and “real world” chemistry.
“Now we can use machine learning to explore data from literature to select new targets, and then the next step: make new medicines,” Cagnoni told the Delaware Business Times. “The field is a little early still, but others are doing a lot of work in this and we decided it was time to accelerate our journey in that space.”
What sets Genesis, and its predictive AI platform called GEMS, apart is that it’s more advanced in technology than the 10 companies Incyte considered. Genesis has already signed collaboration deals with Genentech, Gilead Sciences and Eli Lilly, but Cagnoni said Incyte was impressed with the collaborative approach as well as the technology.
For example, Incyte researchers could – in theory– send Genesis the early structures of a disease target the company is looking to develop a medicine for. Genesis would input the data into its platform to iterate virtually and make possible medicines, which Incyte scientists could work with and send back for further iteration.
“That cycle would greatly accelerate what we could do on our own, and on [Genesis’] end, they’re receiving a lot of chemistry data which helps them accelerate the process,” Cagnoni said. “It’s a combination of virtual and real world that, we think, at least with the technology the way it exists today, might make for the perfect combination in order to make better drugs faster.”
Incyte has been on the search for new breakthroughs, as it has recently secured U.S. Food and Drug Administration approval for Niktimvo, which treats chronic graft-versus-host disease, and Zynyz for anal cancer treatment.
In the past, the company has acquired other companies in a bid to scale but also acquire new drugs - but after Incyte had to shelve the most promising drug acquired from its buyout of Escient Pharmaceuticals, Incyte has opted to focus on emerging technologies this year.
Looking ahead, Cagnoni said there’s a possibility for artificial intelligence to accelerate drug development down the line, namely through drug testing and discovery, which compliments what chemists do in the lab. Biotech companies are also exploring using AI to discover antibodies to be tested, while there's some hope to select the optimal clinical sites to conduct studies or reduce the patient pool in clinical trials by having machine learning build out "digital twins" as an artificical control for the clinical trial.
Cagnoni hesitant to say that it can save months and years yet, but it's opened possibilities to be more efficient.
“Instead of making 10,000 compounds, if we can only get the right one, that obviously saves time. Even better if it turns out to be the right one out of 10,000,” he said.
Genesis has already sent Incyte compounds to test in May, a sign of a strong start. Now it’s just a question whether there will be results from those tests to serve as proof of concept.
