External Evaluation of Population Pharmacokinetic Models and Bayes-Based Dosing of Infliximab

Abstract

Despite the well-demonstrated efficacy of infliximab in inflammatory diseases, treatment failure remains frequent. Dose adjustment using Bayesian methods has shown in silico its interest in achieving target plasma concentrations. However, most of the published models have not been fully validated in accordance with the recommendations. This study aimed to submit these models to an external evaluation and verify their predictive capabilities. Eight models were selected for external evaluation, carried out on an independent database (409 concentrations from 157 patients). Each model was evaluated based on the following parameters: goodness-of-fit (comparison of predictions to observations), residual error model (population weighted residuals (PWRES), individual weighted residuals (IWRES), and normalized prediction distribution errors (NPDE)), and predictive performances (prediction-corrected visual predictive checks (pcVPC) and Bayesian simulations). The performances observed during this external evaluation varied greatly from one model to another. The eight evaluated models showed a significant bias in population predictions (from −7.19 to 7.38 mg/L). Individual predictions showed acceptable bias and precision for six of the eight models (mean error of −0.74 to −0.29 mg/L and mean percent error of −16.6 to −0.4%). Analysis of NPDE and pcVPC confirmed these results and revealed a problem with the inclusion of several covariates (weight, concomitant immunomodulatory treatment, presence of anti-drug antibodies). This external evaluation showed satisfactory results for some models, notably models A and B, and highlighted several prospects for improving the pharmacokinetic models of infliximab for clinical-biological application.

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

“…The predictive performance of infliximab PopPK models was previously externally evaluated in patients with inflammatory diseases, 30 including patients with IBD. 31,32 In the studies of Santacana et al 31 and Schräpel et al, 32 the two models developed by Fasanmade et al 33,34 (using data from the phase III trials) demonstrated the best predictive…”

Impact of Guidelines Regarding Dihydropyrimidine Dehydrogenase (DPD) Deficiency Screening Using Uracil-Based Phenotyping on the Reduction of Severe Side Effect of 5-Fluorouracil-Based Chemotherapy: A Propension Score Analysis

“…To improve the initiation of fluoropyrimidines treatment in DPD deficient patients, pharmacokinetics Bayesian tools could be used [ 41 , 42 , 43 ]. It is well known that plasma concentrations of 5-FU and capecitabine are associated with both side effects and responses.…”

Cost-Effectiveness of Therapeutic Drug Monitoring of Anti-TNF Therapy in Inflammatory Bowel Disease: A Systematic Review

“…However, Model-Informed Precision Dosing (MIPD) is a more precise alternative, based on the use of population pharmacokinetics (PopPK) models and a prospective Bayesian approach to increase the homogeneity in the drug exposure in patients and, therefore, to improve outcomes of treatments [ 61 ]. Some authors have carried out MIPD of adalimumab and infliximab in IBD patients, applying PopPk models found in the literature [ 62 , 63 ]. However, further investigations in this line are required to estimate its cost and compare it with the ones obtained from a TDM strategy.…”