In a new opinion piece for RealClearPolicy, ATR’s Director of Health Policy Isabelle Marchese and Director of Innovation Policy James Erwin argue that artificial intelligence (AI) could save lives by accelerating drug development, lowering costs, and helping researchers pursue treatments for previously difficult-to-treat diseases.
Developing a new drug costs an average of $2.6 billion and takes more than a decade, according to the Information Technology and Innovation Foundation. Most drug candidates fail before reaching patients. AI can help researchers identify promising compounds faster, reduce costly failures, and direct resources toward treatments with greater potential.
“A candidate that fails on a computer costs a few thousand dollars. One that fails in a clinic costs a few hundred million. Every dollar not wasted on a dead end funds the next attempt.”
AI-designed medicines are already advancing through clinical trials. Rentosertib, an AI-designed lung disease drug, progressed from target discovery to a preclinical candidate in just 18 months using fewer than 80 synthesized molecules. A conventional approach can take four and a half years and require thousands of molecules. The authors also report that AI-designed drug candidates have cleared Phase I trials at higher rates than historical industry averages.
“A 2024 analysis found AI-designed molecules cleared Phase I at an 80 to 90 percent rate, well above the 40 to 65 percent average.”
AI is also helping scientists study proteins that have been difficult to target with conventional medicines. Tools such as AlphaFold predict protein structures, while generative AI can help design molecules to interact with those targets. Isomorphic Labs’ nearly $3 billion in partnerships with Eli Lilly and Novartis demonstrates growing investment in these technologies, which could open new avenues for treating diseases such as cancer and Alzheimer’s.
“Most exciting is AI’s ability to treat undruggable diseases. Generally, a drug works by fitting into a ‘pocket’ on a protein’s surface. Many of the proteins that drive cancer and Alzheimer’s have no pocket. In many cases, scientists have known for decades what causes a disease yet simply can’t build a molecule to reach it.”
Beyond drug discovery, AI can improve clinical trials, which account for roughly two-thirds of drug development costs. Predictive models can help researchers evaluate potential treatments and improve trial design, potentially reducing expenses without compromising patient safety. Lower development costs could also make research into rare diseases more economically viable and encourage greater competition among drug developers.
Despite these benefits, policymakers are considering proposals to pause advanced AI research or require additional government approval before AI models can be released. Marchese and Erwin warn that such restrictions could create unnecessary bureaucratic hurdles and delay beneficial innovation. Hypothetical harms should not become an excuse to impede real results in medical research.
“Delaying their use for drug discovery will cost lives rather than save them.”
AI offers an opportunity to accelerate life-saving breakthroughs, reduce development costs, and expand treatment options. Lawmakers should resist unnecessary restrictions that prevent patients from benefiting from medical innovation.
Read the full op-ed here.