This is the first study describing the population PK of adalimumab in patients with JIA. We found that five adalimumab literature models adequately described the concentration-time data from our JIA cohort. However, some overestimation of the observed data in the lower concentration ranges and underestimation of adalimumab concentrations in the higher concentration ranges by the models from Sharma et al. [25] and Ternant et al. [13] reflect the greater variability in adalimumab levels among patients with JIA compared with populations included in prior studies. To further characterize the PK of adalimumab specifically in patients with JIA, its clearance and association with several potential covariates was examined. In these analyses, clearance was estimated at 0.37 L per day per 70 kg, and associations were found with patient body weight, ADA, concomitant use of methotrexate, CRP level, and comorbidity of uveitis during adalimumab treatment.

Our study illustrates a significant resemblance in adalimumab PK among patients with JIA and various cohorts, including healthy adults, adult rheumatoid arthritis patients, and pediatric Crohn’s disease patients. Despite the potential challenges associated with extrapolating PK data from adults to the pediatric population [27, 28], these results suggest the feasibility of such extrapolation for adalimumab, particularly when utilizing standard allometric scaling based on body weight for CL, V1, Q, and V2 [29]. This approach effectively addressed potential differences between adults and children, such as the higher body water content and increased tissue perfusion rate in the latter [28], as evidenced by a significantly improved population PK estimate. In contrast, the disease-related PK differences between pediatric Crohn’s disease and JIA, particularly the leakage of protein (including adalimumab) from an inflamed colon in patients with Crohn’s disease [30], probably introduced complexity in extrapolating this model to the JIA population, demonstrated by a worse fit to the data.

Adalimumab is a known immunogenic protein that can trigger an immune response, and binding of antibodies to adalimumab is known to increase the drug’s clearance [31]. Although the PK model had difficulty to stably identify the covariate effect of ADA in the bootstrap procedure, this study found the same association. However, imputing this covariate effect based on another PK model has several potential drawbacks. Primarily, the variability in ADA assays across different laboratories raises concerns about the accuracy of the imputed ADA estimate, potentially leading to a misspecification of ADA’s true impact on clearance. This concern is particularly pertinent considering the use of a drug-sensitive assay in this study and the one published by Kang et al. [14], which underestimates the prevalence of patients that are ADA-positive [31]. Consequently, correcting too little for the presence of ADA could have resulted in an overestimation of clearance, as this parameter would correct for a potentially inaccurately assumed ADA effect.

As a counterpart to ADA, when adalimumab is coadministered with methotrexate, which most patients in rheumatology take as a concomitant drug, adalimumab clearance was reduced by 28% to 0.27 L per day per 70 kg. This effect of methotrexate aligns with previous studies, as it is a known inhibitor of ADA formation, consequently reducing adalimumab clearance [32, 33]. Furthermore, this diminished clearance is consistent with literature models developed for other indications where methotrexate is concurrently administered [13, 14, 25, 34]. Unfortunately, our JIA dataset did not allow for the determination of a specific dose-effect relationship, which was described previously for the adult rheumatoid arthritis population, were it is recommended to use a methotrexate dose of at least 10 mg/week to mitigate the development of ADA [35, 36].

Clearance also increased with higher CRP level, an association that has been described before [14, 37]. Theoretically, elevated CRP levels, indicative of heightened disease activity and inflammation, may impact antibody breakdown through increased TNF levels and heightened target-mediated drug disposition (TMDD). However, a recent study discredits this notion, revealing comparable TNF levels during TNFi treatment in healthy controls and adult rheumatoid arthritis patients, suggesting that there is no association between CRP and TNF levels, as measured in the circulation, has been demonstrated [38]. In addition, TNF may not even effectively contribute to TMDD, and thus clearance, of TNFi [39]. Therefore, the pathophysiology between CRP level and increased adalimumab clearance remains unknown. The clinical relevance of this association also remains unclear, especially because CRP levels are seldom increased in patients with JIA who usually have low-grade inflammatory disease [40]. Our conducted sensitivity analysis further supports these observations, demonstrating that the parameter estimate of clearance and other covariate estimates remained consistent even when CRP was not included in the PK model.

Finally, a novel association with uveitis was found, and PK analyses concluded an increase in clearance of 44% in these patients. Experience from clinical practice already informed us that patients with JIA with uveitis need more frequent or higher mAbs dosage compared with patients with JIA without uveitis, to control inflammation of the eye (i.e., escalation to weekly adalimumab dosing) [16, 41]. Also, in nonresponding patients with uveitis without JIA, it was already demonstrated that patients benefited from weekly adalimumab injections [42]. This might be explained by the fact that drug exposure resulting from the standard approved dose of adalimumab is inadequate to achieve sufficiently high serum concentrations at the disease site, the eye.

The median (IQR) adalimumab serum level in our cohort was 12.0 (6.2–15.8) mg/L, which is comparable with two earlier publications who reported the adalimumab concentrations in their JIA cohorts [43, 44]. Imagawa et al. described adalimumab concentrations in the range of 0–24.6 mg/L for patients who received either 20 or 40 mg of adalimumab every other week, while Kingsbury et al. [44] reported a mean steady-state adalimumab trough concentration of 7–8 mg/L in young patients with a mean age of 3 years. A comparable mean concentration was found in the simulated dataset at trough after 10 weeks on the standard dose, which was 7.4 ± 5.5 mg/L. The data also revealed a significant variability in adalimumab serum levels among patients with JIA, mirroring observations in the adult population. These findings indicate that the identified covariates may be instrumental in dose optimization for patients with JIA.

Our study has several limitations, primarily attributed to the small sample size and its retrospective nature. Also, concentration measurement was not done in a standardized manner and mainly ordered in case of clinical ineffectiveness. The latter may have led to some bias in data collection, especially with regards to sampling patients with concomitant uveitis. These results should therefore be interpreted with caution. Also, the limited number of available serum measurements made it infeasible to estimate all relevant PK parameters within the JIA population and prospective studies with several PK samples per patient with JIA are warranted. However, using a large literature PK model as a starting point for the analyses, with a previously published structure and fixed key model parameters and focusing on the cohort’s clearance and covariates affecting clearance, did result in the development of a robust model. Not fitting all parameters to this study’s population offers the benefit of enhancing the model’s overall generalizability. However, the downside is that it resulted in a model with a noticeable residual error, complicating its direct application for TDM. This limitation could also be addressed by conducting future PK studies specifically targeted toward the pediatric population and tailored for this particular objective.