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1000 Titel
  • Relative Performance of Volume of Distribution Prediction Methods for Lipophilic Drugs with Uncertainty in LogP Value
1000 Autor/in
  1. Coutinho, Ana Luisa |
  2. Cristofoletti, Rodrigo |
  3. Wu, Fang |
  4. Al Shoyaib, Abdullah |
  5. Dressman, Jennifer |
  6. Polli, James |
1000 Verlag
  • Springer US
1000 Erscheinungsjahr 2024
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-05-08
1000 Erschienen in
1000 Quellenangabe
  • 41(6):1121-1138
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s11095-024-03703-4 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11196289/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:title>Abstract</jats:title> <jats:sec> <jats:title>Purpose</jats:title> <jats:p>The goal was to assess, for lipophilic drugs, the impact of logP on human volume of distribution at steady-state (VD<jats:sub>ss</jats:sub>) predictions, including intermediate fut and Kp values, from six methods: Oie-Tozer, Rodgers-Rowland (tissue-specific Kp and only muscle Kp), GastroPlus, Korzekwa-Nagar, and TCM-New.</jats:p> </jats:sec> <jats:sec> <jats:title>Method</jats:title> <jats:p>A sensitivity analysis with focus on logP was conducted by keeping pKa and fup constant for each of four drugs, while varying logP. VD<jats:sub>ss</jats:sub> was also calculated for the specific literature logP values. Error prediction analysis was conducted by analyzing prediction errors by source of logP values, drug, and overall values.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>The Rodgers-Rowland methods were highly sensitive to logP values, followed by GastroPlus and Korzekwa-Nagar. The Oie-Tozer and TCM-New methods were only modestly sensitive to logP. Hence, the relative performance of these methods depended upon the source of logP value. As logP values increased, TCM-New and Oie-Tozer were the most accurate methods. TCM-New was the only method that was accurate regardless of logP value source. Oie-Tozer provided accurate predictions for griseofulvin, posaconazole, and isavuconazole; GastroPlus for itraconazole and isavuconazole; Korzekwa-Nagar for posaconazole; and TCM-New for griseofulvin, posaconazole, and isavuconazole. Both Rodgers-Rowland methods provided inaccurate predictions due to the overprediction of VD<jats:sub>ss</jats:sub>.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>TCM-New was the most accurate prediction of human VD<jats:sub>ss</jats:sub> across four drugs and three logP sources, followed by Oie-Tozer. TCM-New showed to be the best method for VD<jats:sub>ss</jats:sub> prediction of highly lipophilic drugs, suggesting BPR as a favorable surrogate for drug partitioning in the tissues, and which avoids the use of fup.</jats:p> </jats:sec>
1000 Sacherschließung
lokal Pharmaceutical Preparations/chemistry [MeSH]
lokal logP
lokal lipophilicity
lokal Tissue Distribution [MeSH]
lokal Humans [MeSH]
lokal Pharmacokinetics [MeSH]
lokal Original Research Article
lokal Models, Biological [MeSH]
lokal Triazoles [MeSH]
lokal volume of distribution
lokal Uncertainty [MeSH]
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-3885-3709|https://orcid.org/0000-0003-2619-0343|https://frl.publisso.de/adhoc/uri/V3UsIEZhbmc=|https://frl.publisso.de/adhoc/uri/QWwgU2hveWFpYiwgQWJkdWxsYWg=|https://frl.publisso.de/adhoc/uri/RHJlc3NtYW4sIEplbm5pZmVy|https://orcid.org/0000-0002-5274-4314
1000 Hinweis
  • DeepGreen-ID: 176985cef9ef4254bc29416f66d5d719 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
1000 Label
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    1000 Förderer U.S. Food and Drug Administration |
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1000 Objektart article
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