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

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.

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.

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