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The Cancer Drug Fraction of Metabolism Database
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| Zeitschriftentitel: | CPT: Pharmacometrics & Systems Pharmacology |
|---|---|
| Personen und Körperschaften: | , , , , , , , , , |
| In: | CPT: Pharmacometrics & Systems Pharmacology, 8, 2019, 7, S. 511-519 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Wiley
|
| Schlagwörter: |
| author_facet |
Hua, Liyan Chiang, Chien‐Wei Cong, Wang Li, Jin Wang, Xueying Cheng, Lijun Feng, Weixing Quinney, Sara K. Wang, Lei Li, Lang Hua, Liyan Chiang, Chien‐Wei Cong, Wang Li, Jin Wang, Xueying Cheng, Lijun Feng, Weixing Quinney, Sara K. Wang, Lei Li, Lang |
|---|---|
| author |
Hua, Liyan Chiang, Chien‐Wei Cong, Wang Li, Jin Wang, Xueying Cheng, Lijun Feng, Weixing Quinney, Sara K. Wang, Lei Li, Lang |
| spellingShingle |
Hua, Liyan Chiang, Chien‐Wei Cong, Wang Li, Jin Wang, Xueying Cheng, Lijun Feng, Weixing Quinney, Sara K. Wang, Lei Li, Lang CPT: Pharmacometrics & Systems Pharmacology The Cancer Drug Fraction of Metabolism Database Pharmacology (medical) Modeling and Simulation |
| author_sort |
hua, liyan |
| spelling |
Hua, Liyan Chiang, Chien‐Wei Cong, Wang Li, Jin Wang, Xueying Cheng, Lijun Feng, Weixing Quinney, Sara K. Wang, Lei Li, Lang 2163-8306 2163-8306 Wiley Pharmacology (medical) Modeling and Simulation http://dx.doi.org/10.1002/psp4.12417 <jats:p>This study aims to create a database for quantifying the fraction of metabolism of cytochrome P450 isozymes for cancer drugs approved by the <jats:styled-content style="fixed-case">US </jats:styled-content> 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 <jats:italic>in vitro</jats:italic> 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 <jats:italic>in vitro</jats:italic> 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 <jats:styled-content style="fixed-case">drug–drug interaction</jats:styled-content> pairs.</jats:p> The Cancer Drug Fraction of Metabolism Database CPT: Pharmacometrics & Systems Pharmacology |
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Wiley, 2019 |
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| title |
The Cancer Drug Fraction of Metabolism Database |
| title_unstemmed |
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_short |
The Cancer Drug Fraction of Metabolism Database |
| title_sort |
the cancer drug fraction of metabolism database |
| topic |
Pharmacology (medical) Modeling and Simulation |
| url |
http://dx.doi.org/10.1002/psp4.12417 |
| publishDate |
2019 |
| physical |
511-519 |
| description |
<jats:p>This study aims to create a database for quantifying the fraction of metabolism of cytochrome P450 isozymes for cancer drugs approved by the <jats:styled-content style="fixed-case">US </jats:styled-content> 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 <jats:italic>in vitro</jats:italic> 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 <jats:italic>in vitro</jats:italic> 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 <jats:styled-content style="fixed-case">drug–drug interaction</jats:styled-content> pairs.</jats:p> |
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| author | Hua, Liyan, Chiang, Chien‐Wei, Cong, Wang, Li, Jin, Wang, Xueying, Cheng, Lijun, Feng, Weixing, Quinney, Sara K., Wang, Lei, Li, Lang |
| author_facet | Hua, Liyan, Chiang, Chien‐Wei, Cong, Wang, Li, Jin, Wang, Xueying, Cheng, Lijun, Feng, Weixing, Quinney, Sara K., Wang, Lei, Li, Lang, Hua, Liyan, Chiang, Chien‐Wei, Cong, Wang, Li, Jin, Wang, Xueying, Cheng, Lijun, Feng, Weixing, Quinney, Sara K., Wang, Lei, Li, Lang |
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| container_title | CPT: Pharmacometrics & Systems Pharmacology |
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| description | <jats:p>This study aims to create a database for quantifying the fraction of metabolism of cytochrome P450 isozymes for cancer drugs approved by the <jats:styled-content style="fixed-case">US </jats:styled-content> 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 <jats:italic>in vitro</jats:italic> 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 <jats:italic>in vitro</jats:italic> 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 <jats:styled-content style="fixed-case">drug–drug interaction</jats:styled-content> pairs.</jats:p> |
| doi_str_mv | 10.1002/psp4.12417 |
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| spelling | Hua, Liyan Chiang, Chien‐Wei Cong, Wang Li, Jin Wang, Xueying Cheng, Lijun Feng, Weixing Quinney, Sara K. Wang, Lei Li, Lang 2163-8306 2163-8306 Wiley Pharmacology (medical) Modeling and Simulation http://dx.doi.org/10.1002/psp4.12417 <jats:p>This study aims to create a database for quantifying the fraction of metabolism of cytochrome P450 isozymes for cancer drugs approved by the <jats:styled-content style="fixed-case">US </jats:styled-content> 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 <jats:italic>in vitro</jats:italic> 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 <jats:italic>in vitro</jats:italic> 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 <jats:styled-content style="fixed-case">drug–drug interaction</jats:styled-content> pairs.</jats:p> The Cancer Drug Fraction of Metabolism Database CPT: Pharmacometrics & Systems Pharmacology |
| spellingShingle | Hua, Liyan, Chiang, Chien‐Wei, Cong, Wang, Li, Jin, Wang, Xueying, Cheng, Lijun, Feng, Weixing, Quinney, Sara K., Wang, Lei, Li, Lang, CPT: Pharmacometrics & Systems Pharmacology, The Cancer Drug Fraction of Metabolism Database, Pharmacology (medical), Modeling and Simulation |
| title | 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_short | The Cancer Drug Fraction of Metabolism Database |
| title_sort | the cancer drug fraction of metabolism database |
| title_unstemmed | The Cancer Drug Fraction of Metabolism Database |
| topic | Pharmacology (medical), Modeling and Simulation |
| url | http://dx.doi.org/10.1002/psp4.12417 |