AI Is Reshaping Drug Discovery and the FDA Is Onboard
Artificial intelligence is quickly becoming the new lab assistant in drug discovery, and the U.S. FDA is helping clear the path.
With pressure mounting to cut back on costly and ethically fraught animal testing, pharmaceutical and biotech companies are turning to AI to speed up the development process, slash costs, and predict drug safety more accurately. The shift isn’t on the horizon anymore, it’s already underway.
A New Era in the Lab
Drug development has long relied on animal testing to evaluate a compound’s safety. But the process is slow, expensive, and often doesn’t translate well to human outcomes. Now, the FDA is pushing for a pivot. Within three to five years, animal studies could become the exception, not the rule.
The agency laid out its vision in an April roadmap: computational models, AI-based platforms, and human cell simulations could replace many animal tests—particularly for monoclonal antibody drugs. The potential payoff? Faster timelines, cheaper development, and eventually, more affordable drugs.
Who’s Leading the Charge?
Companies like Certara, Schrodinger, and Recursion Pharmaceuticals are already proving what’s possible.
Certara, which supports drugmakers working on infectious disease therapies, is using AI to simulate how drugs are absorbed, distributed, and whether they could cause toxic side effects. “We’re getting to the point where we don’t actually need to do [animal testing] anymore,” said Patrick Smith, president of drug development solutions at Certara.
Recursion accelerated a cancer drug candidate into clinical trials in just 18 months, less than half the industry’s 42-month average, using its AI-driven discovery platform.
Schrodinger, based in New York, merges AI with physics-based simulations to assess drug toxicology.
Analysts at TD Cowen and Jefferies predict these approaches could eventually cut both costs and development times by more than 50%. That’s a game-changer, considering it currently takes up to 15 years and $2 billion to bring a drug to market.
Old Giants, New Tricks
Legacy players aren’t sitting idle. Charles River Laboratories, one of the world’s largest research contractors, is investing heavily in “new approach methodologies” (NAMs). These include everything from AI modeling to human-based systems like organs-on-chips, tiny devices lined with living human cells that mimic organ function.
Charles River’s NAM portfolio is already pulling in around $200 million annually. Other innovators like InSphero are testing drug safety in 3D liver models made from lab-grown microtissues.
Will Animal Testing Disappear?
Not quite yet. While the FDA’s shift signals major change, experts agree that animal testing won’t vanish overnight. For now, a hybrid model is the most likely path forward: fewer animal studies, supplemented by advanced simulations and human-based models.
Under current FDA guidelines, monoclonal antibodies still require animal testing, typically involving 144 non-human primates per study, with each animal costing about $50,000. These studies can last up to six months, time and money the industry would love to save.
As Brendan Smith, biotech analyst at TD Cowen, puts it: “I don’t think we’ll get to a point immediately, in the near term, where all of a sudden, animal testing is gone entirely.”
The Bottom Line
AI isn’t just disrupting drug development, it’s redefining it. As computational tools become more powerful and regulatory agencies embrace innovation, drugmakers have a real shot at transforming how medicines are brought to market.
Faster. Cheaper. More humane.
That’s the future pharma is betting on.
