This review explores TMDD modeling to enhance predictions of drug behavior in monoclonal antibodies, suggesting improved therapeutic outcomes.
The Target-Mediated Drug Disposition (TMDD) model is an important framework in pharmacokinetics (PK) and pharmacodynamics (PD), providing insights into drug interactions with soluble and membrane-bound targets, particularly for monoclonal antibodies. This paper reviews TMDD modeling specifically focused on monoclonal antibodies targeting soluble ligands, synthesizing existing research and highlighting current advancements. By doing so, we aim to enhance understanding of the application and potential of TMDD modeling in predicting drug behavior and optimizing therapeutic outcomes for soluble targets.
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Nasim et al. (2026) studied this question.
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