Background: Current approved treatments of IPF slow down the progression but are not curative, and drug development for IPF is challenging due to unpredictable disease progression. Disease progression modeling is a tool that can help visualize the trajectory of underlying diseases, describing changes clinically relevant endpoints over time. Forced vital capacity (FVC) is the most commonly accepted clinical endpoint in IPF trials. FVC at baseline and change from baseline have been shown to be significantly associated with progression and survival in IPF patients, therefore can be considered a surrogate marker of disease progression in IPF.

Methods: A nonlinear mixed-effect disease progression model was developed using the placebo arms data from two clinical trials: ASCEND (NCT01366209) and RIFF (NCT01872689) (n=353). External validation of the model is conducted using placebo data from three other clinical trials (TOMORROW, INPULSIS-1 and -2, n=508) to assess the predictive performance of the model.

Result: Longitudinal FVC data was best described by a Weibull function. The model predicts that in the absence of treatment, a typical IPF patient weighing 85kg and aged 67 years old will have an approximate decline of ~257mL from baseline in FVC after ~50 weeks from trial enrollment.

Conclusion: We developed a disease progression model to predict the natural trajectory of FVC over time in IPF patients. Further covariate analyses will be conducted to identify potential prognostic factors that contribute to the progression of IPF and between-subjects variability. The model can be utilized to assess drug effects and leveraged to aid clinical trial designs.