A Model‐Based Approach to Evaluate Anti‐Drug Antibody Impact on Drug Exposure With Biologics: A Case Example With the <scp>CD3</scp> T‐Cell Bispecific Cibisatamab

The administration of biologics can lead to immunogenic responses that trigger anti-drug antibody (ADA) formation. ADAs can decrease drug exposure. A population pharmacokinetic (popPK) model was developed to describe clinical PK data with and without ADA-driven exposure loss with CEA-directed T-cell bispecific antibody cibisatamab. The PK of cibisatamab was evaluated in two clinical studies (as a single agent and in combination with the checkpoint inhibitor atezolizumab) in patients. The popPK model was developed on cibisatamab clinical PK data using the Stochastic Approximation -Expectation Maximization (SAEM) algorithm implemented in Monolix. Cibisatamab's PK followed a two-compartment model with linear clearance decreasing over time and ADA-associated exposure loss. ADA-driven exposure loss was implemented in the model by accounting for ADA formation, reversible binding to cibisatamab, and elimination of both free ADA and the ADA-cibisatamab complex from the central compartment. The impact of ADAs on PK exposure was time-dependent in the model, with the ADA formation described as a function of time (increasing from zero, reaching its estimated maximum value, and possibly decreasing down to 94% of this maximum value in some patients). The final model included a mixture component differentiating patients with and without exposure loss due to ADA formation (75% and 25% of patients, respectively). The investigated patient demographics, dose or dosing schedule, or atezolizumab coadministration were not identified as factors influencing exposure loss due to ADAs. The developed model can be used to differentiate patients with and without ADA-driven exposure loss, as well as for a precise PK characterization in patients even with ADA formation.