Advancing Evidence Generation in Small, Diverse, Understudied Population

Many clinically important patient groups remain systematically underrepresented in drug development. Among these are patients with severe or time-varying organ dysfunction, pregnant and lactating women, children with ultrarare diseases, and people from socioeconomically or geographically underserved communities. Traditional clinical trials frequently exclude such groups. Little direct evidence is generated as a result, leaving benefit-risk and dosing decisions uncertain and trial findings poorly generalizable to the patients who will ultimately receive the drug. No single method closes this gap. This review argues that progress instead comes from integration, combining model-informed drug development, registries and real-world data, external and virtual controls, Bayesian borrowing, and patient-centric trial designs into a coherent totality-of-evidence package. These tools are maturing from a role that supplements clinical data toward one that can, in defined settings, partially replace it. The appropriate approach may differ by population. For example, (1) mechanistic modeling and exposure prediction for organ replacement therapy/changing organ function or from the altered maternal-fetal-infant physiology that makes prospective studies impractical; (2) registry-based external controls and natural history data where patients are too few to randomize; and (3) decentralized, partnership-driven designs to reach populations that structural barriers would otherwise exclude. Three case studies (dose justification across hepatic and renal impairment, evidence generation in women of childbearing potential with chronic autoimmune disease, and a registry-anchored ultrarare pediatric program) illustrated these approaches. Mapped to evolving regulatory frameworks, these strategies can deliver population-appropriate dosing at approval rather than through postmarketing commitments, accelerating equitable access to safe and effective therapies.