Marija Jovanovic1, Valentina Topic Vucenovic2, Maša Roganovic1, Ana Homšek1, Srdan Markovic3, Petar Svorcan3, Katarina Vucicevic1
1University of Belgrade - Faculty of Pharmacy, Department of Pharmacokinetics and Clinical Pharmacy, 2University of Banja Luka - Faculty of Medicine, Department of Pharmacokinetics and Clinical Pharmacy, 3University Hospital Medical Center
Introduction: Adalimumab is a biological drug approved for the treatment of moderately to severely active ulcerative colitis (UC), Crohn’s disease (CD), and various other immune-mediated inflammatory diseases [1]. Numerous factors have been shown to accelerate adalimumab clearance (CL/F) in patients with inflammatory bowel disease (IBD), resulting in reduced drug levels [2]. This reduction may contribute to an elevated risk of suboptimal therapeutic response. Therapeutic drug monitoring (TDM) is usually applied reactively during the maintenance phase to optimise adalimumab therapy in these patients [3]. Identification of factors related to variability in drug levels is essential for effective implementation of TDM in clinical practice. Objectives: The aim of this study was to develop a population pharmacokinetic (PK) model for adalimumab in adult IBD patients and to investigate factors associated with its CL/F. Methods: Data were retrospectively collected from the medical records of 217 adult IBD patients treated at the Clinical Hospital Center “Zvezdara”. Adalimumab was administered subcutaneously, including the induction phase (160 mg at week 0 followed by 80 mg at week 1 or 2) and the maintenance phase (40 mg every or every other week). Alongside adalimumab therapy characteristics, TDM (date and time of blood sampling and measured concentrations), co-therapy, demographic, clinical and available laboratory data were recorded. Levels of anti-adalimumab antibodies (ADA) were categorised as present or absent. Nonlinear mixed-effects modelling was performed for the PK model development and covariate analysis using NONMEM 7.5 software (ICON Development Solutions Inc., Dublin, Ireland). Parameters that could not be estimated with adequate certainty were either fixed to values derived from the literature or assigned informative priors to characterize their values and variability [4]. Evaluation of the final model was performed by internal validation technique. Results: A total of 195 patients with CD (male 49.2%, 39.05 ± 11.91 years, 68.11 ± 1.92 kg) and 22 patients with UC (male 36.4%, 38.64 ± 12.95 years, 67.89 ± 1.68 kg) were included in this analysis. Data for modelling consisted of 832 trough adalimumab concentrations (8.661 ± 5.522 mg/L) obtained predominantly during the maintenance phase. Concentrations below the lower limit of quantification or above the upper limit of quantification were accounted for using the M3 method [5]. A one-compartment model using ADVAN2 TRANS2 subroutine with first-order absorption and elimination best described the data. Based on the literature data, the absorption rate constant was fixed at 0.15 1/day [6]. The estimated CL/F was 0.41 (0.383 – 0.437) L/day, while V/F was 15 (12.96 – 17.04) L for a typical patient. Informative priors were used for V/F and the effect of ADA based on the model developed by Ternant et al [6]. Among tested covariates, only influences of platelets (PLT) and diagnosis on CL/F were statistically significant (p<0.01). According to the final model, patients with ADA-positive status, higher PLT levels and CD diagnosis have higher adalimumab CL/F. Specifically, an increase in PLT level of 100·109/L is associated with a higher CL/F for 16.2%, while ADA-positive patients have a 5.46-fold higher CL/F. The influence of diagnosis needs further investigation, as only 10% of patients in this study had UC. Inclusion of the covariates in the base model decreased inter-individual coefficient of variability for CL/F, and in the final model it was 36.95%. There were no significant impact of weight, body mass index, lean body weight, and faecal calprotectin. The additive and proportional residual errors were 3.8 mg/L and 0.23, respectively. Acceptable model performances were confirmed by adequate diagnostic plots and internal validation. Conclusion: The typical value of adalimumab CL/F in our study is comparable to previous reports [6,7]. This is the first population PK model to demonstrate a positive association between adalimumab CL/F and PLT levels in IBD patients. This finding may suggest that thrombocytosis reflects a higher inflammatory burden, potentially influencing adalimumab elimination, but on the other hand increased disease severity could result from increased elimination of the drug. Nevertheless, recognising factors associated with elevated CL/F may help identify individuals at greater risk of therapeutic failure or loss of response.
[1] Summary Product Characteristics of Humira. Available on: https://www.medicines.org.uk/emc/product/2150/smpc#gref. Last accessed: 6.3.2025. [2] Deyhim T, Cheifetz AS, Papamichael K. Drug clearance in patients with inflammatory bowel disease treated with biologics. J Clin Med. 2023;12(22):7132. [3] de Klaver PAG, Keizer RJ, Ter Heine R, et al. Early at-home measurement of adalimumab concentrations to guide anti-TNF precision dosing: a pilot study. Eur J Drug Metab Pharmacokinet. 2023;48(4):377-85. [4] Chan Kwong AHP, Calvier EAM, Fabre D, Gattacceca F, Khier S. Prior information for population pharmacokinetic and pharmacokinetic/pharmacodynamic analysis: overview and guidance with a focus on the NONMEM PRIOR subroutine. J Pharmacokinet Pharmacodyn. 2020;47(5):431-46. [5] Irby DJ, Ibrahim ME, Dauki AM, et al. (2001). Approaches to handling missing or “problematic” pharmacology data: Pharmacokinetics. CPT Pharmacometrics Syst Pharmacol. 2021;10(4):291-308. [6] Ternant D, Karmiris K, Vermeire S, et al. Pharmacokinetics of adalimumab in Crohn’s disease. Eur J Clin Pharmacol. 2015;71(9):1155-7. [7] Marquez-Megias S, Nalda-Molina R, Más-Serrano P, Ramon-Lopez A. Population pharmacokinetic model of adalimumab based on prior information using real world data. Biomedicines. 2023;11(10):2822.
Reference: PAGE 33 (2025) Abstr 11651 [www.page-meeting.org/?abstract=11651]
Poster: Drug/Disease Modelling - Other Topics