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The Impact of Reference Data Selection for the Prediction Accuracy of Intrinsic Hepatic Metabolic Clearance
Prosil AB, Lannavagen 7, S-14145 Huddinge, Sweden..ORCID iD: 0000-0001-6300-359X
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Science for Life Laboratory, SciLifeLab. Prosil AB, Lannavagen 7, S-14145 Huddinge, Sweden..ORCID iD: 0000-0002-8083-2864
Prosil AB, Lannavagen 7, S-14145 Huddinge, Sweden..
2022 (English)In: Journal of Pharmaceutical Sciences, ISSN 0022-3549, E-ISSN 1520-6017, Vol. 111, no 9, p. 2645-2649Article in journal (Refereed) Published
Abstract [en]

In vitro-in vivo prediction results for hepatic metabolic clearance (CLH) and intrinsic CLH (CLint) vary widely among studies. Reasons are not fully investigated and understood. The possibility to select favorable reference data for in vivo CLH and CLint and unbound fraction in plasma (f(u)) is among possible explanations. The main objective was to investigate how reference data selection influences log in vitro and in vivo CLint-correlations (r(2)). Another aim was to make a head-to-head comparison vs an in silico prediction method. Human hepatocyte CLint-data for 15 compounds from two studies were selected. These were correlated to in vivo CLint estimated using different reported CLH- and f(u)-estimates. Depending on the choice of reference data, r(2) from two studies were 0.07 to 0.86 and 0.06 to 0.79. When using average reference estimates a r(2) of 0.62 was achieved. Inclusion of two outliers in one of the studies resulted in a r(2) of 0.38, which was lower than the predictive accuracy (q(2)) for the in silico method (0.48). In conclusion, the selection of reference data appears to play a major role for demonstrated predictions and the in silico method showed higher accuracy and wider range than hepatocytes for human in vivo CLint-predictions. (C) 2022 Published by Elsevier Inc. on behalf of American Pharmacists Association.

Place, publisher, year, edition, pages
Elsevier BV Elsevier, 2022. Vol. 111, no 9, p. 2645-2649
Keywords [en]
Metabolism, Clearance, In vitro-in vivo correlation, Prediction
National Category
Biochemistry Molecular Biology
Identifiers
URN: urn:nbn:se:uu:diva-483859DOI: 10.1016/j.xphs.2022.06.024ISI: 000843866900010PubMedID: 35793746OAI: oai:DiVA.org:uu-483859DiVA, id: diva2:1693083
Available from: 2022-09-05 Created: 2022-09-05 Last updated: 2025-02-20Bibliographically approved

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