Mouse cancer models have provided critical insights into tumor biology; however, clinical translation of these findings has been challenging. This perspective posits that factors impacting on successful translation start with limitations in capturing human cancer pathophysiology and end with challenges in generating robust translatable preclinical end points. A comprehensive approach that considers clinically relevant mouse models with both an integrated biomarker strategy and a complementary modeling and simulation effort will strengthen the current oncology drug development paradigm
