The Cancer Drug Fraction of Metabolism Database

This study aims to create a database for quantifying the fraction of metabolism of cytochrome P450 isozymes for cancer drugs approved by the US Food and Drug Administration. A reproducible data collection protocol was developed to extract essential information, including both substrate‐depletion and...

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Main Authors: Liyan Hua, Chien‐Wei Chiang, Wang Cong, Jin Li, Xueying Wang, Lijun Cheng, Weixing Feng, Sara K. Quinney, Lei Wang, Lang Li
Format: Article
Language:English
Published: Wiley 2019-07-01
Series:CPT: Pharmacometrics & Systems Pharmacology
Online Access:https://doi.org/10.1002/psp4.12417
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spelling doaj-a86951d6d4b14878afc932feff3a28b12020-11-25T03:15:49ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062019-07-018751151910.1002/psp4.12417The Cancer Drug Fraction of Metabolism DatabaseLiyan Hua0Chien‐Wei Chiang1Wang Cong2Jin Li3Xueying Wang4Lijun Cheng5Weixing Feng6Sara K. Quinney7Lei Wang8Lang Li9College of Automation Harbin Engineering University Harbin ChinaDepartment of Biomedical Informatics College of Medicine The Ohio State University Columbus Ohio USACollege of Automation Harbin Engineering University Harbin ChinaCollege of Automation Harbin Engineering University Harbin ChinaCollege of Automation Harbin Engineering University Harbin ChinaDepartment of Biomedical Informatics College of Medicine The Ohio State University Columbus Ohio USACollege of Automation Harbin Engineering University Harbin ChinaThe Center for Computational Biology and Bioinformatics School of Medicine Indiana University Indianapolis Indiana USACollege of Automation Harbin Engineering University Harbin ChinaDepartment of Biomedical Informatics College of Medicine The Ohio State University Columbus Ohio USAThis study aims to create a database for quantifying the fraction of metabolism of cytochrome P450 isozymes for cancer drugs approved by the US Food and Drug Administration. A reproducible data collection protocol was developed to extract essential information, including both substrate‐depletion and metabolite‐formation data from publicly available in vitro selective cytochrome P450 enzyme inhibition studies. We estimated the fraction of metabolism from the curated data. To demonstrate the utility of this database, we conducted an in vitro drug interaction prediction for the 42 cancer drugs. In the drug–drug interaction prediction, we identified 31 drug pairs with at least one cancer drug in each pair that had predicted area under concentration ratios > 2. We further found clinical drug interaction pieces of evidence in the literature to support 20 of these 31 drug–drug interaction pairs.https://doi.org/10.1002/psp4.12417
collection DOAJ
language English
format Article
sources DOAJ
author Liyan Hua
Chien‐Wei Chiang
Wang Cong
Jin Li
Xueying Wang
Lijun Cheng
Weixing Feng
Sara K. Quinney
Lei Wang
Lang Li
spellingShingle Liyan Hua
Chien‐Wei Chiang
Wang Cong
Jin Li
Xueying Wang
Lijun Cheng
Weixing Feng
Sara K. Quinney
Lei Wang
Lang Li
The Cancer Drug Fraction of Metabolism Database
CPT: Pharmacometrics & Systems Pharmacology
author_facet Liyan Hua
Chien‐Wei Chiang
Wang Cong
Jin Li
Xueying Wang
Lijun Cheng
Weixing Feng
Sara K. Quinney
Lei Wang
Lang Li
author_sort Liyan Hua
title The Cancer Drug Fraction of Metabolism Database
title_short The Cancer Drug Fraction of Metabolism Database
title_full The Cancer Drug Fraction of Metabolism Database
title_fullStr The Cancer Drug Fraction of Metabolism Database
title_full_unstemmed The Cancer Drug Fraction of Metabolism Database
title_sort cancer drug fraction of metabolism database
publisher Wiley
series CPT: Pharmacometrics & Systems Pharmacology
issn 2163-8306
publishDate 2019-07-01
description This study aims to create a database for quantifying the fraction of metabolism of cytochrome P450 isozymes for cancer drugs approved by the US Food and Drug Administration. A reproducible data collection protocol was developed to extract essential information, including both substrate‐depletion and metabolite‐formation data from publicly available in vitro selective cytochrome P450 enzyme inhibition studies. We estimated the fraction of metabolism from the curated data. To demonstrate the utility of this database, we conducted an in vitro drug interaction prediction for the 42 cancer drugs. In the drug–drug interaction prediction, we identified 31 drug pairs with at least one cancer drug in each pair that had predicted area under concentration ratios > 2. We further found clinical drug interaction pieces of evidence in the literature to support 20 of these 31 drug–drug interaction pairs.
url https://doi.org/10.1002/psp4.12417
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