Clinical trials are facing a crisis amid growing delays, diminishing success rates and rising costs. Companies across the stakeholder spread are investing in AI to ease some of the longstanding operational challenges—but new threats of federal funding cuts are raising questions that tech alone can’t answer.
On May 2, the White House unveiled a budget proposal that would cut funding for the National Institutes of Health (NIH) by nearly $18 billion. The nearly 40 percent reduction would eliminate funding for multiple research programs, including the National Institute of Nursing Research and the National Institute on Minority Health and Health Disparities.
As the largest funder of biomedical research in the world, the NIH is considered a global paragon. Budget cuts could lead to permanent cracks in the increasingly fragile research ecosystem, threatening the United States’ position as an international leader in medicine, life sciences and biopharma.
Newsweek asked several clinical research, data and tech professionals if AI could offset the damage. Here’s what it can and can’t solve, according to the experts.
How is AI improving clinical trials and drug discovery?
Pharmaceutical research and development costs have risen substantially over the past few decades, according to recent analyses. In the 1990s, it cost less than $1 billion to develop one new drug. Today, that price has more than tripled to $3.5 billion.
Clinical trial costs are also increasing, with phase III trials costing 30 percent more in 2024 than they did in 2018. Meanwhile, more than one in five trials faced delayed start dates last year—and success rates have fallen under 8 percent.
The numbers don’t paint a pretty picture, according to Orr Inbar, CEO of QuantHealth, a company that uses AI to optimize trial design.
“We’re doing more trials,” Inbar said, “and yet we’re less successful at them, and we’re also less cost efficient in doing them.”
Trials can fail for both clinical and operational reasons. Sometimes, the drugs fail to demonstrate safety or efficacy, while other times, clinical trials run out of funding or struggle to recruit enough patients.
QuantHealth works on both fronts, using data and AI to simulate trial outcomes. This allows pharmaceutical companies to modify their protocol before the trial starts, adjusting the target population or the way the drug is administered to improve their shot at success.
By predicting better candidates and drug targets, AI can help reduce cost and cut back on wasted time and resources throughout the trial process, according to Alister Campbell, vice president of global science and technology at Dotmatics—a scientific software company that helps pharmaceutical, biotech and research organizations gather and organize centralized data.
“We’re seeing AI used as a computational tool that increases the efficiency of all the steps [in trial design],” Campbell said. “By doing that, we can reduce the time it takes to get a drug to market.”
The advent of AI has also helped companies like Walgreens crack the clinical trial space, which once had a high barrier to entry. The retail pharmacy giant launched its clinical trial business in June 2022, helmed by Chief Biopharma Officer Ramita Tandon. It has since engaged more than 17 million patients, educating them on clinical trials, offering participation and helping them to register.
Previously, a human team would have had to sift through Walgreens’ rich network of store, pharmacy and health care transactions to identify patient insights that could be relevant for clinical trials. The company still employs human clinicians to scan the AI model’s output for bias and ensure that its suggested cohorts are applicable to the study and representative of real-world patient populations—but the labor lift is much lower than it would have been without the tech, Tandon said.
“We sit on such a tremendous treasure trove of insights here at Walgreens, and so certainly, we can’t use human labor to be able to canvas that ecosystem to find patients,” Tandon told Newsweek. “AI enables us—with speed and precision—to find those patients for trial.”
AI can even enhance the privacy of de-identified medical data, said Miruna Sasu, president and CEO of COTA Healthcare. Its platform pulls data from electronic medical records, cleans and adjudicates the clinical notes, then returns them to health care organizations for research and development purposes.
An AI agent called CAILIN now sits atop that data and can answer questions about it via a search bar, according to Sasu. This makes the work easier and more cost-effective by eliminating the need for a data scientist. It also helps protect privacy, because a human does not have to comb through individual records to glean insights from the set.
The AI market for drug discovery is “huge,” per Dr. Jo Varshney, CEO of VeriSIM Life—a company that creates digital twins of humans and animals, then uses AI to simulate a drug’s effect on them.
“One of the ways we are trying to circumvent these challenges of [reduced] federal funding is by using a lot of AI,” she said. The tech can still identify novel therapies, patient populations or biomarker discoveries while researchers wait for new avenues of funding (or more solid decisions about existing ones).
“This is where technology can be very helpful, because science cannot wait,” Varshney continued. “We have to keep moving forward, no matter what impacts the external environments create.”
What can’t AI cure in clinical trials and drug discovery?
Still, Varshney said, this is a “very challenging time for any biotech company.” Federal funding is a significant support to the research industry, and without it, innovation is likely to stall.
Inbar, QuantHealth’s CEO, expressed similar concerns. When people hear about resource constraints, they tend to think that AI will step in and fill those gaps—but his experience has been the opposite.
Organizations that cut funds and lay off teams are rarely looking for ways to improve efficiency, Inbar said. Rather, they enter survival mode, reverting to core principles and focusing on getting through the day.
“They get this knee-jerk reaction of fear and stress,” he said, “and that actually, a lot of times, stifles creativity.”
The Food and Drug Administration (FDA) has been working to advance AI integration in the drug discovery process, but if the agency faces the proposed $6.5 billion funding reduction, Inbar predicts those programs will fizzle out.
However, if the FDA is further crunched, companies that focus on regulatory submissions could really shine, according to Inbar. The FDA timeline already drags because of errors in data submissions; more than half of trials submit at least one amendment throughout the process, and the average number of amendment submissions is 4.5 per trial, according to a 2023 study. Companies that use AI to review dossiers and prevent submission errors could help reduce the burden on the regulatory side.
Yet, experts agree that even the most mature AI agent is not a replacement for the knowledge and funding support federal agencies provide. On May 6, the American Association for Cancer Research called upon Congress to halt the “draconian” budget cuts; it assembled a cohort of nearly 400 medical research organizations to organize local meetings, speak with representatives and make the case for strengthening investments in NIH research.
It’s impossible to tell the future, but Inbar believes budget cuts will have an enduring impact—one that outlives this administration, regardless of the next one’s decisions.
“Those people [that are let go] are going to find new jobs, probably in the private sector, where they’re better paid,” he said. “If and when funding comes back, most of them aren’t going to come back to [government jobs].”
“That’s a loss of institutional knowledge that is definitely going to be a lasting effect.”
QuantHealth is one of many brands submitting to Newsweek’s AI Impact Awards, which recognize unique and innovative AI solutions that solve critical issues or advance capabilities across various industries. The awards highlight measurable impacts AI delivers in various business operations, including marketing, customer experience, product development and supply chain optimization.
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