Assessing the Impact of Immunogenicity and Improving Prediction of Trough Concentrations: Population Pharmacokinetic Modeling of Adalimumab in Patients with Crohn's Disease and Ulcerative Colitis.

BACKGROUND AND

objectivePredicting adalimumab pharmacokinetics (PK) for patients impacted by anti-drug antibodies (ADA) has been challenging. The present study assessed the performance of the adalimumab immunogenicity assays in predicting which patients with Crohn's disease (CD) and ulcerative colitis (UC) have low adalimumab trough concentrations; and aimed to improve predictive performance of adalimumab population PK (popPK) model in CD and UC patients whose PK was impacted by ADA.

methodsAdalimumab PK and immunogenicity data obtained from 1459 patients in SERENE CD (NCT02065570) and SERENE UC (NCT02065622) were analyzed. Adalimumab immunogenicity was assessed using electrochemiluminescence (ECL) and enzyme-linked immunosorbent (ELISA) assays. From these assays, three analytical approaches (ELISA concentrations, titer, and signal-to-noise [S/N] measurements) were tested as predictors for classifying patients with/without low concentrations potentially affected by immunogenicity. The performance of different thresholds for these analytical procedures was assessed using receiver operating characteristic curves and precision-recall curves. Based on the results from the most sensitive immunogenicity analytical procedure, patients were classified into PK-not-ADA-impacted and PK-ADA-impacted subpopulations. Stepwise popPK modeling was implemented to fit the PK data to an empirical adalimumab two-compartment model with linear elimination and ADA delay compartments to account for the time delay to generate ADA. Model performance was assessed by visual predictive checks and goodness-of-fit plots.

resultsThe classical ELISA-based classification (with 20 ng/mL ADA as lower threshold) showed a good balance of precision and recall, to determine which patients had at least 30% adalimumab concentrations below 1 µg/mL. Titer-based classification with the lower limit of quantitation (LLOQ) as threshold showed higher sensitivity to classify these patients compared to the ELISA-based approach. Therefore, patients were classified as PK-ADA-impacted or PK-not-ADA impacted using the LLOQ titer threshold. In the stepwise modeling approach ADA-independent parameters were first fit using PK data from titer-PK-not-ADA-impacted population. The identified ADA-independent covariates included the effect of indication, weight, baseline fecal calprotectin, baseline C-reactive protein, baseline albumin on clearance; and sex and weight on volume of distribution of the central compartment. Pharmacokinetic-ADA-driven dynamics were characterized using PK data for the PK-ADA-impacted population. The categorical covariate based on the ELISA classification was the best at describing the additional effect of immunogenicity analytical approaches on ADA synthesis rate. The model was able to adequately describe the central tendency and variability for PK-ADA-impacted CD/UC patients.

conclusionsThe ELISA assay was found to be optimal for capturing impact of ADA on PK. The developed adalimumab popPK model is robust in predicting PK profiles for CD and UC patients whose PK was impacted by ADA.