External Model Performance Evaluation of Twelve Infliximab Population Pharmacokinetic Models in Patients with Inflammatory Bowel Disease

Abstract

Infliximab is approved for treatment of various chronic inflammatory diseases including inflammatory bowel disease (IBD). However, high variability in infliximab trough levels has been associated with diverse response rates. Model-informed precision dosing (MIPD) with population pharmacokinetic models could help to individualize infliximab dosing regimens and improve therapy. The aim of this study was to evaluate the predictive performance of published infliximab population pharmacokinetic models for IBD patients with an external data set. The data set consisted of 105 IBD patients with 336 infliximab concentrations. Literature review identified 12 published models eligible for external evaluation. Model performance was evaluated with goodness-of-fit plots, prediction- and variability-corrected visual predictive checks (pvcVPCs) and quantitative measures. For anti-drug antibody (ADA)-negative patients, model accuracy decreased for predictions > 6 months, while bias did not increase. In general, predictions for patients developing ADA were less accurate for all models investigated. Two models with the highest classification accuracy identified necessary dose escalations (for trough concentrations < 5 µg/mL) in 88% of cases. In summary, population pharmacokinetic modeling can be used to individualize infliximab dosing and thereby help to prevent infliximab trough concentrations dropping below the target trough concentration. However, predictions of infliximab concentrations for patients developing ADA remain challenging.

Multi‐model averaging improves the performance of model‐guided infliximab dosing in patients with inflammatory bowel diseases

“…Currently, there is no well‐established target of classification accuracy for MIPD approach. To the best of our knowledge, classification accuracy has only been included for model predictive performance evaluation for infliximab in Schräpel et al 32 Therefore, defining clinical relevance of these additional analysis tools still requires further investigation to facilitate the translation and appropriate use of the MIPD approaches in clinical care. Third, we also scrutinized the importance of utilizing point‐of‐care testing and the availability of covariate data on the predictive performances.…”

Population pharmacokinetics of cisplatin in small cell lung cancer patients guided with informative priors

“…The sparse concentration measurements in our study precluded the development of an original PK model. Therefore, we evaluated the usefulness of published population PK models for cisplatin in SCLC, by adopting the approach that was recently shown beneficial in informing treatment with other drugs, such as anti-infectives (vancomycin, meropenem, polymyxin B), monoclonal antibodies (infliximab, adalimumab), and imatinib, among others [25,27,28,[34][35][36][37]. In addition, we used informative priors and $PRIOR subroutine in NONMEM, which was demonstrated to produce improved predictive performance of the PK models on sparse datasets, on the population (a priori) and individual (a posteriori) level [29].…”

“…Possible errors in the sampling and infusion time documentation in the early phase could further contribute to higher bias and imprecision, since a recent study demonstrated that even 5 min inaccuracies affect the estimation of volume of distribution in central and peripheral compartment, as well as the intercompartmental clearance [42]. However, the choice of the robust predictive performance parameters (SSPB and ζ) to assess the bias and precision mitigated the outlying error values and possible data inaccuracies in the early phase [33,34].…”

“…1) and the symmetric signed percentage bias (SSPB, Eq. 2), respectively [33,34]; iv) the models with the best predictive performance (lowest ζ and SSPB) were assumed as the most suitable and were combined in a joint multi-prior model with the $PRIOR subroutine in NONMEM ® (Fig. 1).…”

Ulcerative Colitis and Acute Severe Ulcerative Colitis Patients Are Overlooked in Infliximab Population Pharmacokinetic Models: Results from a Comprehensive Review

“…In the selected articles, only two models took ADA into account in a more mechanistic way, seeking to implement immunogenicity impact on clearance and improving model predictions [ 38 , 52 ]. In general, as shown by Schräpel et al, poor predictions are observed for ADA-positive patients compared to ADA-negative in most developed models [ 61 ]. Thus, implementation of more mechanistic models, accounting for the impact of ADA development on PK, as well as on pharmacodynamics, could improve the therapeutic management of ADA-positive patients.…”