Transforming Pediatric Rare Disease Drug Development: Enhancing Clinical Trials and Regulatory Evidence With Virtual Patients

Drug development in pediatric rare diseases is complicated by practical and ethical constraints on clinical trial design, stemming from small, highly heterogeneous, and vulnerable patient populations. Virtual patients (VPs) created with machine‐learning (ML), mechanistically driven computational approaches, or hybrids thereof, have the potential to expedite and maximize the impact of trials. We discuss the potential of VPs to transform the efficiency and impact of clinical trials in pediatric rare diseases, based on adult and pediatric examples.