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A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation
Population factors such as age, gender, ethnicity, genotype and disease state can cause inter-individual variability in pharmacokinetic (PK) profile of drugs. Primarily, this variability arises from differences in abundance of drug metabolizing enzymes and transporters (DMET) among individuals and/o...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609630/ https://www.ncbi.nlm.nih.gov/pubmed/31273226 http://dx.doi.org/10.1038/s41598-019-45778-9 |
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author | Ladumor, Mayur K. Thakur, Aarzoo Sharma, Sheena Rachapally, Aravind Mishra, Sarang Bobe, Priyanka Rao, V. Kameswara Pammi, Praneetha Kangne, Hari Levi, David Balhara, Ankit Ghandikota, Sriram Joshi, Anupama Nautiyal, Vivek Prasad, Bhagwat Singh, Saranjit |
author_facet | Ladumor, Mayur K. Thakur, Aarzoo Sharma, Sheena Rachapally, Aravind Mishra, Sarang Bobe, Priyanka Rao, V. Kameswara Pammi, Praneetha Kangne, Hari Levi, David Balhara, Ankit Ghandikota, Sriram Joshi, Anupama Nautiyal, Vivek Prasad, Bhagwat Singh, Saranjit |
author_sort | Ladumor, Mayur K. |
collection | PubMed |
description | Population factors such as age, gender, ethnicity, genotype and disease state can cause inter-individual variability in pharmacokinetic (PK) profile of drugs. Primarily, this variability arises from differences in abundance of drug metabolizing enzymes and transporters (DMET) among individuals and/or groups. Hence, availability of compiled data on abundance of DMET proteins in different populations can be useful for developing physiologically based pharmacokinetic (PBPK) models. The latter are routinely employed for prediction of PK profiles and drug interactions during drug development and in case of special populations, where clinical studies either are not feasible or have ethical concerns. Therefore, the main aim of this work was to develop a repository of literature-reported DMET abundance data in various human tissues, which included compilation of information on sample size, technique(s) involved, and the demographic factors. The collation of literature reported data revealed high inter-laboratory variability in abundance of DMET proteins. We carried out unbiased meta-analysis to obtain weighted mean and percent coefficient of variation (%CV) values. The obtained %CV values were then integrated into a PBPK model to highlight the variability in drug PK in healthy adults, taking lamotrigine as a model drug. The validated PBPK model was extrapolated to predict PK of lamotrigine in paediatric and hepatic impaired populations. This study thus exemplifies importance of the DMET protein abundance database, and use of determined values of weighted mean and %CV after meta-analysis in PBPK modelling for the prediction of PK of drugs in healthy and special populations. |
format | Online Article Text |
id | pubmed-6609630 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66096302019-07-14 A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation Ladumor, Mayur K. Thakur, Aarzoo Sharma, Sheena Rachapally, Aravind Mishra, Sarang Bobe, Priyanka Rao, V. Kameswara Pammi, Praneetha Kangne, Hari Levi, David Balhara, Ankit Ghandikota, Sriram Joshi, Anupama Nautiyal, Vivek Prasad, Bhagwat Singh, Saranjit Sci Rep Article Population factors such as age, gender, ethnicity, genotype and disease state can cause inter-individual variability in pharmacokinetic (PK) profile of drugs. Primarily, this variability arises from differences in abundance of drug metabolizing enzymes and transporters (DMET) among individuals and/or groups. Hence, availability of compiled data on abundance of DMET proteins in different populations can be useful for developing physiologically based pharmacokinetic (PBPK) models. The latter are routinely employed for prediction of PK profiles and drug interactions during drug development and in case of special populations, where clinical studies either are not feasible or have ethical concerns. Therefore, the main aim of this work was to develop a repository of literature-reported DMET abundance data in various human tissues, which included compilation of information on sample size, technique(s) involved, and the demographic factors. The collation of literature reported data revealed high inter-laboratory variability in abundance of DMET proteins. We carried out unbiased meta-analysis to obtain weighted mean and percent coefficient of variation (%CV) values. The obtained %CV values were then integrated into a PBPK model to highlight the variability in drug PK in healthy adults, taking lamotrigine as a model drug. The validated PBPK model was extrapolated to predict PK of lamotrigine in paediatric and hepatic impaired populations. This study thus exemplifies importance of the DMET protein abundance database, and use of determined values of weighted mean and %CV after meta-analysis in PBPK modelling for the prediction of PK of drugs in healthy and special populations. Nature Publishing Group UK 2019-07-04 /pmc/articles/PMC6609630/ /pubmed/31273226 http://dx.doi.org/10.1038/s41598-019-45778-9 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ladumor, Mayur K. Thakur, Aarzoo Sharma, Sheena Rachapally, Aravind Mishra, Sarang Bobe, Priyanka Rao, V. Kameswara Pammi, Praneetha Kangne, Hari Levi, David Balhara, Ankit Ghandikota, Sriram Joshi, Anupama Nautiyal, Vivek Prasad, Bhagwat Singh, Saranjit A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation |
title | A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation |
title_full | A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation |
title_fullStr | A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation |
title_full_unstemmed | A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation |
title_short | A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation |
title_sort | repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (pbpk) modelling and simulation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609630/ https://www.ncbi.nlm.nih.gov/pubmed/31273226 http://dx.doi.org/10.1038/s41598-019-45778-9 |
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