Improved Population Pharmacokinetic Model for Predicting Optimized Infliximab Exposure in Pediatric Inflammatory Bowel Disease

Background: Many pediatric patients with inflammatory bowel disease (IBD) lose response to infliximab (IFX) within the first year, and achieving a minimal target IFX trough concentration is associated with higher remission rates and longer durability. Population pharmacokinetic (PK) modeling can predict trough concentrations for individualized dosing. The object of this study was to refine a population PK model that accurately predicts individual IFX exposure during maintenance therapy using longitudinal real-practice data.

Methods: We exported data from the electronic health records of pediatric patients with IBD treated with originator IFX at a single center between January 2011 and March 2017. Subjects were divided into discovery and validation cohorts. A population PK model was built and then validated.

Results: We identified 228 pediatric patients with IBD who received IFX and had at least 1 drug concentration measured, including 135 and 93 patients in the discovery and validation cohorts, respectively. Weight, albumin, antibodies to IFX (ATI) detected by a drug-tolerant assay, and erythrocyte sedimentation rate (ESR) were identified as covariates significantly associated with IFX clearance and incorporated into the model. The model exhibited high accuracy for predicting target IFX trough concentrations with an area under the receiver operating characteristic curve (AUROC) of 0.86 (95% confidence interval [CI], 0.81-0.91) for population-based predictions without prior drug-level input. Accuracy increased further for individual-based predictions when prior drug levels were known, with an AUROC of 0.93 (95% CI, 0.90-0.97).

Conclusions: A population PK model utilizing weight, albumin, ordinal drug-tolerant ATI, and ESR accurately predicts IFX trough concentrations during maintenance therapy in real-practice pediatric patients with IBD. This model, which incorporates dynamic clinical information, could be used for individualized dosing decisions to increase response durability.