Optimizing Early Ophthalmology Clinical Trials: Home OCT and Modeling Can Reduce Sample Size by 20% to 40%

Purpose: Early-stage clinical trials for major retinal diseases face challenges due to substantial interpatient variability, end points with high intrapatient variability, and prolonged follow-up periods required to detect treatment effects. This study explores whether integrating home optical coherence tomography (OCT) monitoring with pharmacokinetic/pharmacodynamic (PK/PD) modeling can reduce clinical trial sample size. Methods: A population PK/PD model was developed using longitudinal central subfield thickness data from a home OCT study. Monte Carlo simulations and bootstrapping were used to evaluate the impact of different monitoring strategies on sample size requirements to detect a simulated effect size of approximately 50-µm central subfield thickness reduction over an active comparator drug. Results: To reliably detect this effect, traditional biweekly in-clinic monitoring required 41 to 54 patients per arm, whereas home OCT monitoring only required 33 to 35 patients per arm, representing a 20% to 40% sample size reduction. Conclusions: These findings highlight the potential for home OCT and PK/PD modeling to improve trial efficiency and patient convenience while maintaining statistical power. Translational Relevance: By reducing sample size requirements while maintaining statistical power, this approach can streamline clinical trials, expediting the development of new retinal therapies and improving patient access to treatment.