This study presents a translational modeling framework designed to predict tumor size dynamics in cancer patients undergoing anticancer treatment, using data from patient-derived xenograft (PDX) mice. In the first step, a population tumor growth inhibition (TGI) model to estimate the distribution of exponential tumor growth rates and anticancer drug potency in PDX mice was built. Then, model parameters were allometrically scal...

Tumor volume doubling time (TVDT) has been shown to be a potential surrogate marker of biological tumor activity. However, its availability in clinics is strongly limited due to ethical and practical reasons, as its assessment requires at least two subsequent tumor volume measurements in untreated patients. Here, a translational modeling framework to predict TVDT distributions in untreated cancer patient populations from tumor...

Covariate identification is an important step in the development of a population pharmacokinetic/pharmacodynamic model. Among the different available approaches, the stepwise covariate model (SCM) is the most used. However, SCM is based on a local search strategy, in which the model-building process iteratively tests the addition or elimination of a single covariate at a time given all the others. This introduces a heuristic t...