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Introduction: Forced vital capacity is the only registrational endpoint in idiopathic pulmonary fibrosis clinical trials. As most new treatments will be administered on top of standard of care, estimating treatment response will become more challenging. We developed a simulation model to quantify variability associated with forced vital capacity decline., Methods: The model is based on publicly available clinical trial summary and home spirometry data. A single, illustrative trial setting is reported. Model assumptions are 400 subjects randomised 1:1 to investigational drug or placebo over 52 weeks, 50% of each group receiving standard of care (all-comer population), and a 90-mL treatment difference in annual forced vital capacity decline. Longitudinal profiles were simulated and the impact of varying clinical scenarios evaluated., Results: Power to detect a significant treatment difference was 87-97%, depending on the analysis method. Repeated measures analysis generally outperformed analysis of covariance and mixed linear models, particularly with missing data (as simulated data were non-linear). A 15% yearly random dropout rate led to 0.6-5% power loss. Forced vital capacity decline-related dropout introduced greater power loss (up to 12%), as did subjects starting/stopping standard of care or investigational drug. Power was substantially lower for a 26-week trial due to the smaller assumed treatment effect at week 26 (sample size would need doubling to reach a power similar to that of a 52-week trial)., Conclusions: Our model quantifies forced vital capacity decline and associated variability, with all the caveats of background therapy, permitting robust power calculations to inform future idiopathic pulmonary fibrosis clinical trial design., Funding: Galapagos NV (Mechelen, Belgium).