More than 50 bispecific antibodies are in oncology clinical development with a large diversity in formats, directed at a range of immune and tumor targets. Bispecifics have demonstrated the potential for enhanced efficacy and reduced systemic toxicity. However, they are complex modalities with challenges to overcome in early clinical trials, including selection of relevant starting doses and dose escalation strategy due to non-intuitive exposure-response relationships. In this context, prediction and management of cytokine-release syndrome (CRS) is important.
Multiple factors can contribute to between-patient variability, including tumor type, avidity, receptor expression, effector-to-target-cell ratio, and presence of soluble target.
Mechanistic, quantitative systems pharmacology (QSP) models are increasingly being used in the design of bispecifics and to guide translation research, clinical trial design, dose regimen optimization, and patient selection.
Following a general introduction, we shared a case study on using model-informed clinical development to unlock the therapeutic potential of mosunetuzumab (a CD20/CD3 bispecific antibody) to illustrate the application of QSP in drug development and regulatory decision-making.
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