Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.1021/acs.chemrestox.0c00349 |
| Document | author version |
| Title (Primary) | Prediction of unbound fractions for in vitro–in vivo extrapolation of biotransformation data |
| Author | Krause, S.; Goss, K.-U. |
| Source Titel | Chemical Research in Toxicology |
| Year | 2021 |
| Department | AUC |
| Volume | 34 |
| Issue | 1 |
| Page From | 7 |
| Page To | 11 |
| Language | englisch |
| Topic | T9 Healthy Planet |
| Supplements | https://pubs.acs.org/doi/10.1021/acs.chemrestox.0c00349?goto=supporting-info |
| Abstract | For in vitro–in vivo extrapolation of biotransformation data, the different sorptive environments in vitro and in vivo need to be considered. The most common approach for doing so is using the ratio of unbound fractions in vitro and in vivo. In the literature, several algorithms for prediction of these unbound fractions are available. In this study, we present a theoretical evaluation of the most commonly used algorithms for prediction of unbound fractions in S9 assays and blood and compare prediction results with empirical values from the literature. The results of this analysis prove a good performance of “composition-based” algorithms, i.e. algorithms that represent the inhomogeneous composition of in vitro assay and in vivo system and describe sorption to the individual components (lipids, proteins, water) in the same way. For strongly sorbing chemicals, these algorithms yield constant values for the ratio of unbound fractions in vitro and in vivo. This is mechanistically plausible, because in these cases, the chemicals are mostly bound, and the ratio of unbound fractions is determined by the volume ratio of sorbing components in both phases. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=24104 |
| Krause, S., Goss, K.-U. (2021): Prediction of unbound fractions for in vitro–in vivo extrapolation of biotransformation data Chem. Res. Toxicol. 34 (1), 7 - 11 10.1021/acs.chemrestox.0c00349 |
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