Only one in ten potential drugs successfully navigates the rigorous process of clinical trials to reach the market. Scientists are now exploring artificial intelligence to expand the datasets available for testing and improve success rates. This involves creating virtual patient cohorts and utilizing "digital twins"—computer-generated replicas of individuals—to simulate trial conditions. These AI-generated cohorts offer a way to augment or even partially replace traditional clinical trials, potentially reducing costs and accelerating timelines. The goal is to gain deeper insights into how a drug might perform across a broader and more diverse patient population. While not a replacement for human trials, these digital counterparts offer a valuable new tool in pharmaceutical research. This method could represent a significant shift in drug development, helping bring vital medications to patients more efficiently.