When the Cure Already Exists
A conversation with David Fajgenbaum on drug repurposing, rare disease, and why the answers might already be on the shelf
I sat down with David Fajgenbaum for the latest episode of Precision Signals for a deeply personal conversation.
David was a third-year medical student and former Division I quarterback when his organs began to shut down. He was read his last rites five times. The diagnosis was idiopathic multicentric Castleman disease, a rare condition in a gray zone between autoimmunity and malignancy, with no reliable treatment. So David did something extraordinary. He started banking his own blood, ran experiments between hospitalizations, traced a signaling pathway in his own tissue, and identified a decades-old transplant drug that no one had ever tried for Castleman disease.
Last month marked 12 years in remission.
Years ago, I invited David to speak at the FDA’s Oncology Center of Excellence, and he left a mark on our entire team. He challenged us to rethink rare diseases, drug repurposing, and the gap between the knowledge in the literature and the knowledge that actually reaches patients. One story from our conversation captures this well: a 2013 paper showed high PD-L1 expression in angiosarcoma. Three years passed before anyone acted on it. David’s team did. That patient has now been in remission for 10 years on a PD-L1 inhibitor.
Today David co-leads Every Cure, a nonprofit using AI to score every approved drug against every known disease. 4,000 drugs. 18,000 diseases. Millions of combinations. The premise is simple and, I think, correct: many of the treatments patients need already exist. The system just hasn’t connected the dots.
I wish I’d known of this organization, this program, in 2023. My wife was originally misdiagnosed with a very large pulmonary embolism in the major artery connecting the left lung to the heart, very near the heart. The original diagnosis was reasonable, in keeping with the old adage about hoofbeats, horses and zebras.
Only after the PE didn’t respond to blood thinners (and, frankly, after continuous pressure from us to consider a differential diagnosis), she was diagnosed with Pulmonary Artery Sarcoma.
A pneumonectomy and partial resection of the artery, followed by aggressive chemotherapy and radiation therapy, bought her some time. I’m told, and I accept, that this ultra rare cancer was not curable (the cancer, after all, is in the artery wall, inside the circulation system and hence beyond any possibility of localization, isolation), but perhaps there’s some obscure match in this database with a treatment which could have bought even a bit more time.
I’d be interested to see more study of this system, its successes, strengths and weaknesses, including success rates when there is an apparent match.
The angiosarcoma example is the whole thesis in miniature: the PD-L1 signal sat in the literature for three years before anyone acted, and that lag, not the absence of a finding, is the failure mode. The hard part of the Every Cure model is what happens after the score. A high drug-disease match still needs someone to run the confirmatory study and a clinician willing to prescribe off-label, and those incentives are exactly what is missing for off-patent compounds.
Fajgenbaum's own case worked because he was both the scientist and the patient.
Scaling that is the real challenge.