Factors influencing monoclonal antibody pharmacokinetics across varying immune perturbations

Jonathon DeBonis1, Anthony Davis1, Zeshi Wang1

  • 1Department of Bioengineering, Rice University, Houston, TX, USA.

The development of continuous-release devices or injectables for the long-term delivery of biologics is of great interest, especially monoclonal antibodies (mAbs) that require frequent, high-dose injections. Preclinical testing of these technologies in murine models is necessary for clinical translation; however, xenogeneic responses to the mAb and foreign body responses to the implants or injectables can confound results. Immune system knockout (KO) models that affect immune cells are often used in these experiments, but the effects of KO models on mAb pharmacokinetics (PK) are not well characterized. Here, we investigated the PK profile of the human mAb 3BNC117 after intravenous, subcutaneous, and intraperitoneal injections in four mouse strains: BL6, BCD, RAG2, and NSG mice. Noncompartmental analysis was used to quantify differences in PK between each mouse strain. Strikingly, both BL6 and NSG mice exhibited significantly higher mAb clearance compared to the other two strains. To better understand these differences, we developed a minimal physiologically based PK model of mAb PK incorporating FcγR interaction in the peripheral tissue and the formation of anti-drug antibodies. The estimated model parameters demonstrate that the rapid clearance in the BL6 and NSG strains can be explained by the formation of anti-drug antibodies and increased FcγR abundance in peripheral tissues, respectively. We then used simple allometric scaling relationships to assess which strains were reasonably predictive of human mAb PK. The scaled parameters obtained from BCD and RAG2 mice led to reasonably accurate human predicted PK, whereas the parameters obtained from NSG and BL6 mice did not. These results emphasize that the mechanistic differences influencing NSG and BL6 PK must be considered when assessing the translatability of data.

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