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Physiologically based pharmacokinetic modeling for predicting irinotecan exposure in human body

Colorectal cancer is the third leading cause of cancer-related deaths in the United States. Treatment of colorectal cancer remains a challenge to clinicians as well as drug developers. Irinotecan, a Camptothecin derivative, is successfully used for the treatment of this rapidly progressing malignanc...

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Autores principales: Fan, Yingfang, Mansoor, Najia, Ahmad, Tasneem, Khan, Rafeeq Alam, Czejka, Martin, Sharib, Syed, Yang, Dong-Hua, Ahmed, Mansoor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5564636/
https://www.ncbi.nlm.nih.gov/pubmed/28636998
http://dx.doi.org/10.18632/oncotarget.18380
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author Fan, Yingfang
Mansoor, Najia
Ahmad, Tasneem
Khan, Rafeeq Alam
Czejka, Martin
Sharib, Syed
Yang, Dong-Hua
Ahmed, Mansoor
author_facet Fan, Yingfang
Mansoor, Najia
Ahmad, Tasneem
Khan, Rafeeq Alam
Czejka, Martin
Sharib, Syed
Yang, Dong-Hua
Ahmed, Mansoor
author_sort Fan, Yingfang
collection PubMed
description Colorectal cancer is the third leading cause of cancer-related deaths in the United States. Treatment of colorectal cancer remains a challenge to clinicians as well as drug developers. Irinotecan, a Camptothecin derivative, is successfully used for the treatment of this rapidly progressing malignancy and finds its place in the first line of therapeutic agents. Irinotecan is also effective in treating SCLC, malignant glioma and pancreatic adenocarcinoma. However, its adverse effects limit its clinical application. Mainly metabolized by hepatic route, and excreted through biliary tract, this dug has been found to possess high variation in patients in its pharmacokinetic (PK) profile. Physiologically based pharmacokinetic (PBPK) models using compartmental approach have attained their position to foresee the possible PK behavior of different drugs before their administration to patients and such models have been proposed for several anticancer agents. In this work, we used WB-PBPK technology to develop a model in a population of tumor patients who used IV irinotecan therapy. This model depicted the concentration of drug and its pharmacologically active metabolite in human body over a specific period of time. Knowledge about pharmacokinetic parameters is extracted from this profile and the model is evaluated by the observed results of clinical study presented in literature. The predicted behavior of the drug by this approach is in good agreement with the observed results and can aid in further exploration of PK of irinotecan in cancer patients, especially in those concomitantly suffer from other morbidity.
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spelling pubmed-55646362017-08-23 Physiologically based pharmacokinetic modeling for predicting irinotecan exposure in human body Fan, Yingfang Mansoor, Najia Ahmad, Tasneem Khan, Rafeeq Alam Czejka, Martin Sharib, Syed Yang, Dong-Hua Ahmed, Mansoor Oncotarget Research Paper Colorectal cancer is the third leading cause of cancer-related deaths in the United States. Treatment of colorectal cancer remains a challenge to clinicians as well as drug developers. Irinotecan, a Camptothecin derivative, is successfully used for the treatment of this rapidly progressing malignancy and finds its place in the first line of therapeutic agents. Irinotecan is also effective in treating SCLC, malignant glioma and pancreatic adenocarcinoma. However, its adverse effects limit its clinical application. Mainly metabolized by hepatic route, and excreted through biliary tract, this dug has been found to possess high variation in patients in its pharmacokinetic (PK) profile. Physiologically based pharmacokinetic (PBPK) models using compartmental approach have attained their position to foresee the possible PK behavior of different drugs before their administration to patients and such models have been proposed for several anticancer agents. In this work, we used WB-PBPK technology to develop a model in a population of tumor patients who used IV irinotecan therapy. This model depicted the concentration of drug and its pharmacologically active metabolite in human body over a specific period of time. Knowledge about pharmacokinetic parameters is extracted from this profile and the model is evaluated by the observed results of clinical study presented in literature. The predicted behavior of the drug by this approach is in good agreement with the observed results and can aid in further exploration of PK of irinotecan in cancer patients, especially in those concomitantly suffer from other morbidity. Impact Journals LLC 2017-06-06 /pmc/articles/PMC5564636/ /pubmed/28636998 http://dx.doi.org/10.18632/oncotarget.18380 Text en Copyright: © 2017 Fan et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (http://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Fan, Yingfang
Mansoor, Najia
Ahmad, Tasneem
Khan, Rafeeq Alam
Czejka, Martin
Sharib, Syed
Yang, Dong-Hua
Ahmed, Mansoor
Physiologically based pharmacokinetic modeling for predicting irinotecan exposure in human body
title Physiologically based pharmacokinetic modeling for predicting irinotecan exposure in human body
title_full Physiologically based pharmacokinetic modeling for predicting irinotecan exposure in human body
title_fullStr Physiologically based pharmacokinetic modeling for predicting irinotecan exposure in human body
title_full_unstemmed Physiologically based pharmacokinetic modeling for predicting irinotecan exposure in human body
title_short Physiologically based pharmacokinetic modeling for predicting irinotecan exposure in human body
title_sort physiologically based pharmacokinetic modeling for predicting irinotecan exposure in human body
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5564636/
https://www.ncbi.nlm.nih.gov/pubmed/28636998
http://dx.doi.org/10.18632/oncotarget.18380
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