Ponce-Bobadilla Ana Victoria, Stodtmann Sven, Chen Mong-Jen, Winzenborg Insa, Mensing Sven, Blaes Jonas, Haslberger Tobias, Laplanche Loic, Dreher Ingeborg, Mostafa Nael M
AbbVie Deutschland GmbH & Co. KG, Ludwigshafen, Germany.
AbbVie, 1 N. Waukegan Road, North Chicago, IL, 60064, USA.
Clin Pharmacokinet. 2023 Apr;62(4):623-634. doi: 10.1007/s40262-023-01221-x. Epub 2023 Mar 11.
Predicting 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.
Adalimumab 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.
The 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.
The 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.
预测受抗药物抗体(ADA)影响的患者的阿达木单抗药代动力学(PK)具有挑战性。本研究评估了阿达木单抗免疫原性检测在预测哪些克罗恩病(CD)和溃疡性结肠炎(UC)患者阿达木单抗谷浓度较低方面的性能;旨在提高阿达木单抗群体药代动力学(popPK)模型在PK受ADA影响的CD和UC患者中的预测性能。
分析了从SERENE CD(NCT02065570)和SERENE UC(NCT02065622)的1459例患者中获得的阿达木单抗PK和免疫原性数据。使用电化学发光(ECL)和酶联免疫吸附(ELISA)检测评估阿达木单抗免疫原性。从这些检测中,测试了三种分析方法(ELISA浓度、滴度和信噪比[S/N]测量)作为对可能受免疫原性影响的低浓度患者进行分类的预测指标。使用受试者工作特征曲线和精确召回率曲线评估这些分析程序不同阈值的性能。根据最敏感的免疫原性分析程序的结果,将患者分为PK未受ADA影响和PK受ADA影响的亚组。实施逐步popPK建模,将PK数据拟合到具有线性消除和ADA延迟室的经验性阿达木单抗二室模型,以考虑产生ADA的时间延迟。通过视觉预测检查和拟合优度图评估模型性能。
基于经典ELISA的分类(以20 ng/mL ADA作为下限阈值)在确定哪些患者至少30%的阿达木单抗浓度低于1 μg/mL方面显示出精度和召回率的良好平衡。以定量下限(LLOQ)为阈值的基于滴度的分类与基于ELISA的方法相比,对这些患者进行分类时显示出更高的敏感性。因此,使用LLOQ滴度阈值将患者分类为PK受ADA影响或PK未受ADA影响。在逐步建模方法中,首先使用来自滴度-PK未受ADA影响群体的PK数据拟合ADA独立参数。确定的ADA独立协变量包括适应证、体重、基线粪便钙卫蛋白、基线C反应蛋白、基线白蛋白对清除率的影响;以及性别和体重对中央室分布容积的影响。使用PK受ADA影响群体的PK数据表征药代动力学-ADA驱动的动力学。基于ELISA分类的分类协变量在描述免疫原性分析方法对ADA合成速率的额外影响方面表现最佳。该模型能够充分描述PK受ADA影响的CD/UC患者的中心趋势和变异性。
发现ELISA检测最适合捕捉ADA对PK的影响。所开发的阿达木单抗popPK模型在预测PK受ADA影响的CD和UC患者的PK概况方面具有稳健性。