Antibody-drug conjugates are important molecular entities in the treatment of cancer, with 8 antibody-drug conjugates approved by the US Food and Drug Administration since 2000 and many more in early-and late-stage clinical development. These conjugates combine the target specificity of monoclonal antibodies with the potent anticancer activity of small-molecule therapeutics. The complex structure of antibody-drug conjugates poses unique challenges to pharmacokinetic (PK) and pharmacodynamic (PD) characterization because it requires a quantitative understanding of the PK and PD properties of multiple different molecular species (eg, conjugate, total antibody, and unconjugated payload) in different tissues. Quantitative clinical pharmacology using mathematical modeling and simulation provides an excellent approach to overcome these challenges, as it can simultaneously integrate the disposition, PK, and PD of antibody-drug conjugates and their components in a quantitative manner. In this review, we highlight diverse quantitative clinical pharmacology approaches, ranging from system models (eg, physiologically based pharmacokinetic [PBPK] modeling) to mechanistic and empirical models (eg, population PK/PD modeling for single or multiple analytes, exposure-response modeling, platform modeling by pooling data across multiple antibody-drug conjugates). The impact of these PBPK and PK/PD models to provide insights into clinical dosing justification and inform drug development decisions is also highlighted.