
How Regulators Assess Substantial Evidence When Trial Populations Are Too Small for Traditional Designs
In this video interview, Mwango Kashoki, MD, MPH, senior vice president and global head of regulatory strategy at Parexel, breaks down how the FDA evaluates substantial evidence of effectiveness for individualized therapies in ultra-rare conditions, and why that determination depends on the totality of mechanistic, biomarker, and clinical outcome data rather than trial numbers alone.
Full interview summary
In a recent video interview with Applied Clinical Trials, Mwango Kashoki, MD, MPH, senior vice president and global head of regulatory strategy at Parexel, discussed the FDA's plausible mechanism
Kashoki went on to explain how the
She addressed the vulnerabilities of master protocol designs under this framework, cautioning that basket designs require careful biological justification for each mutation and condition being studied, and that differences in patient age, dosing, disease severity, and progression can quickly undermine what looks straightforward in concept. On external controls and natural history data, she stressed that heterogeneity in disease course and patient characteristics is a persistent confounding risk, and that achieving meaningful patient matching typically requires a natural history database far larger than the interventional study itself.
Kashoki closed with practical guidance for sponsors navigating the framework in its current draft state, urging early agency engagement before first-in-human trials, robust non-clinical programs, adaptive and seamless trial designs, and a clearly articulated confirmatory evidence package that gives regulators what they need to make a substantial evidence determination.




