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

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.

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.

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.

These findings highlight the potential for home OCT and PK/PD modeling to improve trial efficiency and patient convenience while maintaining statistical power.

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.