The pharmaceutical industry often focuses on developing novel drugs, yet a vast, untapped resource lies within the thousands of medicines already approved for use. Physician-scientist David Fajgenbaum has pioneered a movement to repurpose these existing drugs for new conditions, arguing that many treatments we need are already available – we just haven’t connected them to the right diseases yet.
The Treatment Gap
Despite advancements in modern medicine, a significant treatment gap remains. Of the roughly 18,000 known diseases, only 4,000 have approved drugs. This leaves tens of thousands of conditions with no viable treatment options for patients. The reality is that biology doesn’t adhere to strict pharmaceutical classifications; a drug designed for one ailment may offer benefits for entirely unrelated conditions.
The Incentive Problem
The primary barrier to drug repurposing isn’t scientific, but economic. Once a drug becomes generic, there’s little financial incentive for companies to fund clinical trials proving its efficacy for new uses. Conducting these trials costs millions, and without guaranteed profits, research often goes unfunded, even if lives could be saved.
Fajgenbaum’s own near-fatal battle with Castleman disease underscored this problem. After exhausting all standard treatments, he independently researched existing drugs and discovered sirolimus, an immunosuppressant already on the market, could potentially regulate the immune pathway driving his condition. The drug saved his life, sparking his mission to uncover hidden cures within existing pharmaceuticals.
AI as a Catalyst
Traditionally, identifying repurposing opportunities required years of manual literature review. Now, Fajgenbaum’s nonprofit Every Cure is leveraging artificial intelligence to accelerate this process. Their platform can analyze the entire biomedical knowledge base, evaluating 75 million drug-disease combinations in a matter of hours. This field, termed “computational pharmacophenomics,” scores the likelihood of each drug treating each disease, allowing researchers to focus on the most promising leads.
The shift to repurposing could dramatically reduce treatment timelines. Instead of spending a decade or more developing new molecules, researchers can fast-track existing drugs with known safety profiles, analyze real-world data, and move directly into trials. Autoimmune diseases, with their shared biological pathways, are particularly ripe for breakthroughs using this approach.
A Paradigm Shift
Fajgenbaum’s work challenges the conventional wisdom that innovation in medicine always requires creating something entirely new. The future may lie in re-examining existing resources and asking more effective questions. AI-driven drug repurposing isn’t just a faster path to treatment; it’s a fundamental re-thinking of how we approach disease and healthcare.
