Pharmacodynamic Models for Predicting Weight Loss Efficacy in Early-Phase Trials

Abstract

Early-phase clinical trials for anti-obesity drugs are often too short to observe significant weight loss, making it difficult to assess efficacy and inform go/no-go decisions. Pharmacodynamic (PD) modeling offers a framework for predicting long-term weight loss trajectories from short-term data by characterizing the relationship between drug exposure, pharmacological effect, and body weight dynamics. This white paper reviews established and emerging PD modeling approaches used in early-phase obesity trials, including indirect response models, energy balance models, and mechanism-based frameworks. We discuss how these models can be applied to integrate biomarker data, simulate weight loss trajectories, and support dose selection and trial design. Case examples illustrate the application of PD modeling to predict weight loss outcomes from early-phase data, demonstrating how modeling and simulation can bridge the gap between short-term pharmacological signals and long-term clinical endpoints. By enabling more informed early-phase decision-making, PD modeling approaches have the potential to reduce attrition in obesity drug development and enable greater scientific and operational efficiency.