ArticleCPT: pharmacometrics & systems pharmacology2026
A Generalized Minimal PBPK-PD Model of Bispecific Antibodies: Case Studies and Applications in Drug Development.
Article in CPT: pharmacometrics & systems pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- A Generalized Minimal PBPK-PD Model of Bispecific Antibodies: Case Studies and Applications in Drug Development.CPT: pharmacometrics & systems pharmacology · 2026Article
- Interleukin-17 in disease pathogenesis and therapy: recent advances in targeted drug design and medicinal chemistry.Frontiers in pharmacology · 2026Review
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5 authors.
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Abstract
Bispecific antibodies (bsAbs), for which each arm binds a distinct molecular target, are developed to engage soluble and cell surface targets in different therapeutic indications. Three key examples of mechanisms of action (MoA) for bsAbs are (1) immune cell engagers that foster immune cell interactions with target cells, (2) bispecifics that use one arm to increase specificity/localization to desired tissues to reduce on-target off-tissue toxicity, and (3) bispecifics that use two different arms to neutralize different disease targets. Understanding the pharmacokinetic (PK) profiles and target engagement of bsAbs poses unique challenges due to the existence of multiple targets with distinct biological properties. Here, we present a generalized minimal physiologically based pharmacokinetic (mPBPK) model to capture and predict the PK and target engagement of bsAbs across multiple tissues. First, we model the clinical PK and pharmacodynamic (PD) data for an anti-IL-13/IL-17 bsAb to capture and explain the PD response in the soluble cytokine target levels. Second, we model and simulate the PK-PD of the anti-CD20/CD3 T cell engaging antibody, mosunetuzumab, which acts via trans-binding between cell targets on B- and T-lymphocytes. Third, we use the model to explore case studies for other bsAb approaches to demonstrate the impact of binding affinity and avidity on both PK and target engagement and to provide insights into drug design. Overall, our work yields a model with example applications to advance the use of mechanistic modeling for early PK and target engagement predictions as well as for optimization of bsAb design.
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