Prediction of Oral Bioavailability in Rats: Transferring Insights from in Vitro Correlations to (Deep) Machine Learning Models Using in Silico Model Outputs and Chemical Structure Parameters-Reference-Cited by-同舟云学术

Prediction of Oral Bioavailability in Rats: Transferring Insights from in Vitro Correlations to (Deep) Machine Learning Models Using in Silico Model Outputs and Chemical Structure Parameters

Published:2019-11-01 Issue:11 Volume:59 Page:4893-4905
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Schneckener Sebastian¹,Grimbs Sergio¹,Hey Jessica¹,Menz Stephan²,Osmers Maren²,Schaper Steffen¹,Hillisch Alexander³,Göller Andreas H.³^ORCID

Affiliation:

1. Bayer AG, Engineering & Technology, Applied Mathematics, 51368 Leverkusen, Germany

2. Bayer AG, R&D, Pharmaceuticals, Research Pharmacokinetics, 13342 Berlin, Germany

3. Bayer AG, Pharmaceuticals, R&D, Computational Molecular Design, 42096 Wuppertal, Germany

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.9b00460

Reference49 articles.

1. Advances in oral drug delivery: improved bioavailability of poorly absorbed drugs by tissue and cellular optimization

2. Molecular Properties That Influence the Oral Bioavailability of Drug Candidates

3. Population-Based Mechanistic Prediction of Oral Drug Absorption

4. Technologies to Improve the Solubility, Dissolution and Bioavailability of Poorly Soluble Drugs

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