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

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 mode...

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Autores principales: Schräpel, Christina, Kovar, Lukas, Selzer, Dominik, Hofmann, Ute, Tran, Florian, Reinisch, Walter, Schwab, Matthias, Lehr, Thorsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468301/
https://www.ncbi.nlm.nih.gov/pubmed/34575443
http://dx.doi.org/10.3390/pharmaceutics13091368
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author Schräpel, Christina
Kovar, Lukas
Selzer, Dominik
Hofmann, Ute
Tran, Florian
Reinisch, Walter
Schwab, Matthias
Lehr, Thorsten
author_facet Schräpel, Christina
Kovar, Lukas
Selzer, Dominik
Hofmann, Ute
Tran, Florian
Reinisch, Walter
Schwab, Matthias
Lehr, Thorsten
author_sort Schräpel, Christina
collection PubMed
description 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.
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spelling pubmed-84683012021-09-27 External Model Performance Evaluation of Twelve Infliximab Population Pharmacokinetic Models in Patients with Inflammatory Bowel Disease Schräpel, Christina Kovar, Lukas Selzer, Dominik Hofmann, Ute Tran, Florian Reinisch, Walter Schwab, Matthias Lehr, Thorsten Pharmaceutics Article 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. MDPI 2021-08-31 /pmc/articles/PMC8468301/ /pubmed/34575443 http://dx.doi.org/10.3390/pharmaceutics13091368 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Schräpel, Christina
Kovar, Lukas
Selzer, Dominik
Hofmann, Ute
Tran, Florian
Reinisch, Walter
Schwab, Matthias
Lehr, Thorsten
External Model Performance Evaluation of Twelve Infliximab Population Pharmacokinetic Models in Patients with Inflammatory Bowel Disease
title External Model Performance Evaluation of Twelve Infliximab Population Pharmacokinetic Models in Patients with Inflammatory Bowel Disease
title_full External Model Performance Evaluation of Twelve Infliximab Population Pharmacokinetic Models in Patients with Inflammatory Bowel Disease
title_fullStr External Model Performance Evaluation of Twelve Infliximab Population Pharmacokinetic Models in Patients with Inflammatory Bowel Disease
title_full_unstemmed External Model Performance Evaluation of Twelve Infliximab Population Pharmacokinetic Models in Patients with Inflammatory Bowel Disease
title_short External Model Performance Evaluation of Twelve Infliximab Population Pharmacokinetic Models in Patients with Inflammatory Bowel Disease
title_sort external model performance evaluation of twelve infliximab population pharmacokinetic models in patients with inflammatory bowel disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468301/
https://www.ncbi.nlm.nih.gov/pubmed/34575443
http://dx.doi.org/10.3390/pharmaceutics13091368
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