B ehind the creation of every pill or injection are thousands of man-hours and years of research, trials, and failures. The time between a drug’s discovery and the moment a doctor can prescribe it is 15 years, so big medical announcements provide very little hope for those suffering from the disease it is designed to treat.
Adityo Prakash wants to change that.
As CEO of Verseon, a pharmaceutical company that’s spent the better part of 20 years creating not a wonder drug but the fundamental scientific platform that will discover and build the era-defining treatments of the future, he and his team of over a dozen pioneers in life sciences, physics, and mathematics have created a groundbreaking approach to drug discovery that blends deep quantum modeling and their own AI learning model.
They’re not interested in making tiny tweaks to existing therapies; they’re working to speed up the creation of revolutionary new treatments. Verseon is transforming the capabilities of modern medicine and saving millions of future lives.
Verseon’s vision of a faster, more efficient drug discovery process stems from the team’s shared belief that the industry’s current methods require a significant overhaul. While many companies point to AI as a solution, Prakash notes that AI alone cannot create something it hasn’t already seen, so how can anyone using it create something entirely new?
“We design completely novel drugs atom-by-atom simply outside the reach of the rest of the pharmaceutical industry,” Prakash says.
They accomplish this with deep quantum modeling, which predicts how new drug molecules will bind to a disease-causing protein. This computer-based modeling treats creating new therapies as a physics problem and generates drug candidates with the desired therapeutic properties. This challenge has held up the industry for 35 years and continues to plague most labs.
Prakash says it has been notoriously difficult to predict how a drug will interact with a protein in water, but Verseon’s deep quantum modeling allows them to do just that. Their platform, which combines deep quantum modeling with lab tests and AI, also tailors each property of the drug in a way that best serves the patient.
“Because of the deep quantum modeling at the atomic level, we find islands of useful data that nobody has ever seen,” he says. This accelerated process gives them the recipe to create a treatment and proceed to preclinical testing. Here, Verseon documents new reactions, collects that data, and feeds it to their proprietary AI, which further tweaks and optimizes the properties and suggests changes. The findings keep generating additional novel data. “My AI is working on data nobody else has,” he says.
Prakash says their solution required the right AI tools because small-molecule drug discovery is the “realm of small and sparse data. For small-molecule drugs you can take as a pill, the number of possibilities is simply too large, and you never have big data,” he explains. “We had to develop our own AI tools to successfully work with small data. We are as much a high-tech company as we are a biotech company.”
This unique scientific platform is more than a competitive advantage; it enables them to see and do what has never been done: systematically develop drugs faster than anyone else, put the drugs through routine tests, and get them into clinical trials while other companies are still stuck in the discovery phase.
It should be noted that other pharma companies do tout their advances using AI. Still, Prakash says their AI-generated drugs are what the industry calls “me-too” tweaks, or slight improvements to existing formulas, not significant breakthroughs. “The great medicines of the future will not be found this way,” he cautions.
As of January 2024, Verseon has 16 drug candidates focusing on two major disease categories (cardiometabolic disorders and cancer). One candidate is in clinical trials, 4 more are ready to enter trials, and another 8 will be ready in the next 18 months, a feat never thought possible in the pharma world. One drug will limit the amount of internal bleeding that people taking blood thinners for the treatment of heart disease experience.
The leading blood thinners cause these patients to develop large, dark bruises from any bump or cut, and the Verseon drug will reduce the bleeding to near-normal levels. Doctors who have seen the drug in action are already asking when they can start prescribing it because it will improve the lives of millions. “When our drugs come to market, it will be malpractice to prescribe anything else. That’s what we mean when we say we want to change the standard of care for diseases we address.”
No other company has Verson’s deep quantum modeling, and no pharmaceutical library can access their lab data. To date, every program that Verseon has started has resulted in viable candidates after the final round of optimization using AI. Moving forward, they’ll use AI-driven analysis to decide which drug candidates work better for specific patient populations and take the personalization of drugs to a whole new level. Verseon is on a mission to pursue drugs with highly desirable therapeutic properties that no one thought were possible.
Verseon is already transforming what modern medicine can do. They’re reaching a point where their drugs are in a position to touch billions of lives. Adityo Prakash knows that how their discoveries are packaged, prescribed, or handled by physicians is out of his control, but his team can develop better therapeutic medical options to treat diseases or even prevent them. “We’re trying to change what’s possible,” he says. “There is a massive need for us to do better.”