Warfarin, a commonly prescribed oral anticoagulant medication, is highly effective in treating deep vein thrombosis and pulmonary embolism. However, the clinical dosing of warfarin is complicated by high inter-individual variability in drug exposure and response and its narrow therapeutic index. CYP2C9 genetic polymorphism and drug-drug interactions (DDIs) are substantial contributors to this high variability of warfarin pharmacokinetics (PK), among numerous factors. Building a physiological-based pharmacokinetic (PBPK) model for warfarin is not only critical for a mechanistic characterization of warfarin PK, but also useful for investigating the complicated dose-exposure relationship of warfarin. Thus, the objective of this study was to develop a PBPK model for warfarin which integrates information regarding CYP2C9 genetic polymorphisms and their impact on DDIs. Generic PBPK models for both Sand R-warfarin, the two enantiomers of warfarin, were constructed in R with the mrgsolve package. As expected, a generic PBPK model structure did not adequately characterize the warfarin PK profile collected up to 15 days following the administration of single oral dose of warfarin, especially for S-warfarin. However, following the integration of an empirical targetmediated drug disposition (TMDD) component, the PBPK-TMDD model well characterized the PK profiles collected for both S-and R-warfarin in subjects with different CYP2C9 genotypes.Following the integration of enzyme inhibition and induction effects, the PBPK-TMDD model also characterized the PK profiles of both S-and R-warfarin in various DDI settings. The developed mathematic framework may be useful in building algorithms to better inform the clinical dosing of warfarin.