Smarter trial designs could cut study sizes by 60% for heart disease

Imagine a clinical trial that needs far fewer people to prove a new drug works. That’s the promise of a new approach that uses genetic risk scores to focus on volunteers most likely to get sick. Researchers tested this idea using UK Biobank data, simulating how it would work for coronary artery disease, glaucoma, and inflammatory bowel disease. They found that by enrolling only people in the top 25% of genetic risk, the required sample size for some trials could drop by about 60% for heart disease and 78% for IBD. This could also speed up how quickly trials gather results. But the benefit wasn’t universal; for glaucoma, the most restrictive approach didn’t add extra gain because the smaller sample size made it harder to see a difference. This was a computer simulation, not a real trial, and the best risk threshold depends on the specific disease. Still, it shows how genetic data might help build faster, more efficient studies in the future.