Predicting tumor dynamics in treated patients from patient-derived-xenograft mouse models: a translational model-based approach.

ABSTRACT: 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 scaled from mice to humans to inform a TGI model predicting tumor size dynamics in cancer patients. Longitudinal tumor dynamics predicted by the PDX-informed TGI model were expressed in terms of tumor progression events to allow validation against literature time-to-progression (TTP) data. The proposed approach was tested on two case studies: gemcitabine treatment for pan

SUBMITTER: Ronchi D 

PROVIDER: S-EPMC12003590 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature