Impact of rise in anti-drug antibodies on the pharmacokinetics of the monoclonal antibody adalimumab
T. van Donge, J.A.A Reijers, J. Burggraaf, J. Stevens (1)*
(1) Centre for Human Drug Research (CHDR), Leiden, The Netherlands * (2) Current affiliation, department of Clinical Pharmacology, University Medical Center Groningen, Groningen, The Netherlands
Objectives: To quantitate the high variability in pharmacokinetics (PK) of the monoclonal antibody adalimumab, with specific focus on the role of anti-drug antibodies on elimination process. Methods: PK and immunogenic data were obtained from a double blind, 3-parallel groups, single-center biosimilarity trial (n=198) of adalimumab, in which healthy volunteers received, single subcutaneous dose of 40mg of test (ONS-3010) or reference (Humira® EU or Humira® US) product[1]. Population PK modelling was performed using FOCEI in NONMEM 7.3[2]. Structural models with one, two or three compartments including combinations of linear and non-linear absorption and clearance were fitted to the data to determine best structural model. Between-subject variability was assumed log-normal distributed and residual error structures were tested (proportional, additive and combined). Data on body weight, LBW, BSA, BMI, height, age, dosing formulation and neutralizing capacity of anti-drug antibodies was used for covariate analysis. Potential covariate correlations were visually and statistically identified (Pearson’s r2>0.3) before these covariates were formally tested based on improvement in model performance. Results: A one-compartmental model with linear absorption and Michaelis-Menten elimination best described the individual plasma concentration over time profiles. Interindividual variability was identified on absorption rate constant (Ka), central volume of distribution (V) and Michaelis-Menten constant (Km) with coefficients of variation of 65.9%, 20.1% and 110%, respectively. Residual variability was best described by a proportional error structure. Allometric scaling on V significantly improved the fit and was incorporated in the model. A direct effect of anti-drug antibodies on the maximum rate of elimination improved the model fit (decrease in OFV of 440 points). Dosing formulations did not contain significant correlations with any of the PK parameters. All PK parameters were estimated with high precision (RSE<30%). Condition number was 10.3, demonstrating no model instability. All parameter estimated lie well within the 95% confidence interval of the bootstrap analysis (98.3% successful runs). The development of neutralizing anti-drug antibodies resulted in reduced exposure of 41.63% in the lower (2.5%-percentile) bound of the AUC. Conclusions: PK model suggests that a rise in anti-drug antibodies significantly increases the elimination of adalimumab and therefore reduces exposure, which may partly explain the difference in treatment responses between patients.
References:
[1] Dillingh MR, Reijers JAA, Malone KE, Burggraaf J, Bahrt K, Yamashita L, Rehrig C, Moerland M Clinical evaluation of Humira® biosimilar ONS-3010 in healthy volunteers: focus on pharmacokinetics and pharmacodynamics. Frontiers in Immunology (2016) 7:508
[2] Beal SL, Sheiner LB, Boeckmann AJ, and Bauer RJ (eds) NONMEM 7.3.0 Users Guides. (1989–2013). ICON Development Solutions, Hanover, MD.
