Legacy data sharing to improve drug safety assessment: the eTOX project-Reference-Cited by-同舟云学术

Legacy data sharing to improve drug safety assessment: the eTOX project

Published:2017-10-13 Issue:12 Volume:16 Page:811-812
ISSN:1474-1776
Container-title:Nature Reviews Drug Discovery
language:en
Short-container-title:Nat Rev Drug Discov

Author:

Sanz Ferran, ,Pognan François,Steger-Hartmann Thomas,Díaz Carlos,Cases Montserrat,Pastor Manuel,Marc Philippe,Wichard Joerg,Briggs Katharine,Watson David K.,Kleinöder Thomas,Yang Chihae,Amberg Alexander,Beaumont Maria,Brookes Anthony J.,Brunak Søren,Cronin Mark T. D.,Ecker Gerhard F.,Escher Sylvia,Greene Nigel,Guzmán Antonio,Hersey Anne,Jacques Pascale,Lammens Lieve,Mestres Jordi,Muster Wolfgang,Northeved Helle,Pinches Marc,Saiz Javier,Sajot Nicolas,Valencia Alfonso,van der Lei Johan,Vermeulen Nico P. E.,Vock Esther,Wolber Gerhard,Zamora Ismael

Publisher

Springer Science and Business Media LLC

Subject

Drug Discovery,Pharmacology,General Medicine

Link

http://www.nature.com/articles/nrd.2017.177.pdf

Reference5 articles.

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2. Carbonell, P. et al. Hepatotoxicity prediction by systems biology modeling of disturbed metabolic pathways using gene expression data. ALTEX 34, 219–234 (2017)10.14573/altex.1602071.

3. Harvey, J. et al. Management of organic impurities in small molecule medicinal products: deriving safe limits for use in early development. Regul. Toxicol. Pharmacol. 84, 116–123 (2017)10.1016/j.yrtph.2016.12.011.

4. Carrió, P. et al. Applicability Domain Analysis (ADAN): a robust method for assessing the reliability of drug property predictions. J. Chem. Inf. Model. 54, 1500–1511 (2014).

5. Hewitt, M. et al. Ensuring confidence in predictions: a scheme to assess the scientific validity of in silico models. Adv. Drug Deliv. Rev. 86, 101–111 (2015)10.1016/j.addr.2015.03.005.

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