(T-052) Modeling the Time-Varying Impact of Anti-Drug Antibody Formation on the Pharmacokinetics of a Human Monoclonal Antibody in a Preclinical Study

JOSIAH RYMAN, PhD – Associate director, Research and Development Institute, EMD Serono; VIBHA JAWA, PhD – Executive Director, Nonclinical Disposition and Bioanalysis, Bristol Myers Squibb; BERND MEIBOHM, PhD – Professor, Pharmaceutical Sciences, University of Tennessee Health Science Center

Objectives: Administration of human monoclonal antibodies (mAbs) to animals during preclinical drug development may be accompanied by an immune response. This may lead to the formation of anti-drug antibodies (ADA) against the mAb. ADA forms an immune complex with the mAb and may reduce the systemic exposure of the mAb by triggering an immune complex-mediated clearance. This complicates the accurate assessment of preclinical pharmacokinetics (PK), and may prevent toxicology studies from establishing safe exposure ranges of the mAb in study animals.

The objective of this work is to model the time-course of ADA formation and its impact on the PK profile in rats after administration of a human mAb at two different dose levels and aggregation states, and under concomitant administration of different immunosuppressive regimens.

Methods: A population PK (PPK) model was developed using mAb (erenumab used as model drug) concentration and ADA data from 80 Sprague Dawley rats in two 12-week long preclinical studies (n=40 in each study). In study 1, rats were randomly divided into 5 groups that received subcutaneous administration of 10 mg/kg of the mAb in monomeric form. Animals in the first group only received mAb monomer, whereas animals in the other groups received one of four different immunosuppressive regimens of methotrexate or a combination of tacrolimus and sirolimus (TAC/SIR). In study 2, animals received 1 mg/kg mAb monomer or 1 mg/kg mAb in aggregated form with and without TAC/SIR immunosuppression. The best model was chosen based on lowest objective function, Akaike information criterion and goodness-of-fit plots.

Results: The PK of mAb was best described by a one-compartment model with linear elimination (CL/F 1.78 mL/day [4.3% RSE]) and uniform distribution (Vd/F 32.9 mL [5.5% RSE]). The absorption was characterized using a first-order process (Ka 0.82 day^-1 [7.6% RSE]) with lag time (0.016 day [26.6% RSE]). Two separate residual error models were used for the two studies. Aggregation type was identified as a covariate for CL and Ka. mAb in its aggregated form led to ~2.78-fold (6.9% RSE) higher CL and ~0.19-fold (13.1% RSE) lower Ka compared to mAb monomer. The effect of ADA was modeled as a time-varying covariate for CL, where it was incorporated as a dichotomous covariate at each of the 35 observation time points. ADA was found to have a significant impact on the CL and mAb systemic exposure. CL in the 14 ADA+ animals was found to be 8 to 80-fold higher compared to ADA- animals. The model well-characterized the observed large variation in magnitude of ADA effect. This was described by a large inter-individual variability of ~1140% on the CL of ADA+ animals.

Conclusions: The PPK model adequately described the PK and impact of ADA on the mAb PK in rats. This analysis captures the time-varying impact of ADA formation on the PK of a mAb and could serve as a base model for mechanistic modeling of immune system that drive the generation of ADA.

Citations: None