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Experimental NAMs provide insights into drug disposition, pharmacological activity, and disease biology that are difficult or impossible to obtain from traditional animal\u2010based models. Physiologically based pharmacokinetic (PBPK) and quantitative systems pharmacology (QSP) models represent a complementary class of computational NAMs. Together, experimental and computational NAMs form an integrated translational framework that converts mechanistic biological data into quantitative predictions of human exposure, efficacy, and safety across the drug development continuum. In this state\u2010of\u2010the\u2010art review, we present our perspective on the current and emerging role of PBPK and QSP as computational NAMs, supported by case studies spanning a range of regulatory and clinical applications. Across all case studies, the integration of human\u2010relevant experimental data into mechanistic models is shown to be the critical determinant of translational success. 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