Optimizing Geographic Atrophy Clinical Trial Design: The Role of Run-In Phases, Single-Arm Architectures, and Functional Endpoints

MedXY Editorial Team•May 20, 2026•Clinical Updates

In silico power analyses demonstrate that incorporating a 9-month run-in phase can reduce the required sample size for a 90% powered RCT from 156 to just 26 participants.
Single-arm trial designs, which compare treatment phases against a patient’s own run-in natural history, offer the highest statistical efficiency, potentially requiring as few as 14 participants.
Mesopic microperimetry (MMP) significantly outperforms visual acuity as a functional outcome measure, requiring far smaller cohorts to detect significant disease progression.
Emerging AI-driven longitudinal modeling and glial-cell-based biomarkers provide new avenues for precision patient stratification and growth rate prediction.

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This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

In silico power analyses demonstrate that incorporating a 9-month run-in phase can reduce the required sample size for a 90% powered RCT from 156 to just 26 participants.
Single-arm trial designs, which compare treatment phases against a patient’s own run-in natural history, offer the highest statistical efficiency, potentially requiring as few as 14 participants.
Mesopic microperimetry (MMP) significantly outperforms visual acuity as a functional outcome measure, requiring far smaller cohorts to detect significant disease progression.
Emerging AI-driven longitudinal modeling and glial-cell-based biomarkers provide new avenues for precision patient stratification and growth rate prediction.