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Abraham, M. H.; Ibrahim, A.; Zhao, Y.; Acree, W. E. A data base for partition of volatile organic compounds and drugs from blood/plasma/serum to brain, and an LFER analysis of the data. J. Pharm. Sci. 2006, 95, 10, 2091–2100.

QsarDB Repository

Abraham, M. H.; Ibrahim, A.; Zhao, Y.; Acree, W. E. A data base for partition of volatile organic compounds and drugs from blood/plasma/serum to brain, and an LFER analysis of the data. J. Pharm. Sci. 2006, 95, 10, 2091–2100.

QDB archive DOI: 10.15152/QDB.132   DOWNLOAD

QsarDB content

Property logBB: Blood-brain distribution

Compounds: 328 | Models: 3 | Predictions: 3

Eq2: Model for drug-like chemicals, in vivo i

Regression model (regression)

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Name Type n

R2

σ

Training set training 233 0.751 0.322
Eq4: Model for VOCs, in vitro i

Regression model (regression)

Open in:QDB Explorer QDB Predictor

Name Type n

R2

σ

Training set training 95 0.697 0.202
Eq5: Model for all chemicals, in vivo and in vitro i

Regression model (regression)

Open in:QDB Explorer QDB Predictor

Name Type n

R2

σ

Training set training 328 0.753 0.297

Citing

When using this data, please cite the original article and this QDB archive:

  • Abraham, M. H.; Ibrahim, A.; Zhao, Y.; Acree, W. E. A data base for partition of volatile organic compounds and drugs from blood/plasma/serum to brain, and an LFER analysis of the data. J. Pharm. Sci. 2006, 95, 2091–2100. http://dx.doi.org/10.1002/jps.20595

  • Kahn, I. QDB archive #132. QsarDB repository, 2015. http://dx.doi.org/10.15152/QDB.132

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Title: Abraham, M. H.; Ibrahim, A.; Zhao, Y.; Acree, W. E. A data base for partition of volatile organic compounds and drugs from blood/plasma/serum to brain, and an LFER analysis of the data. J. Pharm. Sci. 2006, 95, 10, 2091–2100.
Abstract: Literature values of the in vivo distribution (BB) of drugs from blood, plasma, or serum to rat brain have been assembled for 207 compounds (233 data points). Wefind that data on in vivo distribution from blood, plasma, and serum to rat brain can all be combined. Application of our general linear free energy relationship (LFER) to the 207 compounds yields an equation in log BB, with R2=0.75 and a standard deviation, SD, of 0.33 log units. An equation for a training set predicts the test set of data with a standard deviation of 0.31 log units. We further find that the in vivo data cannot simply be combined with in vitro data on volatile organic and inorganic compounds, because there is a systematic difference between the two sets of data. Use of an indicator variable allows the two sets to be combined, leading to a LFER equation for 302 compounds (328 data points) with R2=0.75 and SD=0.30 log units. A training equation was then used to predict a test set with SD=0.25 log units.
URI: http://hdl.handle.net/10967/132
http://dx.doi.org/10.15152/QDB.132
Date: 2015-01-14


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