{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,26]],"date-time":"2026-07-26T22:17:53Z","timestamp":1785104273560,"version":"3.55.0"},"reference-count":33,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T00:00:00Z","timestamp":1740182400000},"content-version":"vor","delay-in-days":21,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["ascpt.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clinical Translational Sci"],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The use of model\u2010informed precision dosing to personalize infliximab has been shown to improve both the acquisition of concentration targets and clinical outcomes during maintenance. Current iterations of infliximab pharmacokinetic models include time\u2010varying covariates of drug clearance, however, not accounting for the expected improvements in the covariates can lead to indiscriminate use of higher infliximab doses and imprecise drug exposure. The aim was to identify changes in the four biomarkers associated with infliximab clearance (Xiong et\u00a0al. model) and determine if integration of these dynamic changes would improve model performance during induction and early maintenance. We analyzed two cohorts of children receiving infliximab for Crohn's Disease. The <jats:italic>E<\/jats:italic><jats:sub>max<\/jats:sub> method was used to assess time\u2010varying changes in covariates. Model performance (observed vs. predicted infliximab concentrations) was evaluated using median percentage error (bias) and median absolute percentage error (precision). The combined cohorts included 239 Crohn's disease patients. We found from baseline to dose 4, the maximum changes in weight, albumin, erythrocyte sedimentation rate, and neutrophil CD64 were 4.7%, +11.7%, \u221262.4%, and \u221226.5%, respectively. We also found the use of baseline covariates alone to forecast future trough concentration was inferior to the <jats:italic>E<\/jats:italic><jats:sub>max<\/jats:sub> time\u2010varying method with a significant improvement observed in bias (doses 2, 3, and 4) and precision (doses 2 and 4). The integration of the four time\u2010varying biomarkers of drug clearance with pharmacokinetic modeling improved the accuracy and precision of the predictions. This novel strategy may be key to improving drug exposure, minimizing indiscriminate dosing strategies, and reducing healthcare costs.<\/jats:p>","DOI":"10.1111\/cts.70086","type":"journal-article","created":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T12:38:51Z","timestamp":1740227931000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Integrating early response biomarkers in pharmacokinetic models: A novel method to individualize the initial infliximab dose in patients with Crohn's disease"],"prefix":"10.1111","volume":"18","author":[{"given":"Abigail","family":"Samuels","sequence":"first","affiliation":[{"name":"Department of Internal Medicine, Department of Veterans Affairs University of Cincinnati School of Medicine  Cincinnati Ohio 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