Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling has emerged as a powerful approach to support drug development and precision medicine by providing a mechanistic framework to understand variability in drug exposure and response. PBPK models integrate drug properties with physiological and population variability, including differences in demographics, organ function, disease status, metabolic capacity, and concomitant medications, enabling characterization of inter-individual variability, prediction of exposure–response relationships, optimization of dosing strategies, and support of regulatory decision-making. By leveraging virtual populations and advanced simulations, Virtual Twin approaches in PBPK modeling are emerging as a means to advance precision dosing and accelerate the transition from one-size-fits-all treatment toward individualized therapies. Virtual Twins are individualized in silico representations of patients generated by integrating patient-specific characteristics with mechanistic PBPK/PD models. This presentation will first describe the development of virtual populations and their role in capturing human variability, followed by selected case studies illustrating PBPK modeling applications and the emerging use of Virtual Twins to support personalized treatment strategies.