International Journal of Molecular Sciences | |
Inroads to Predict |
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Katharine Briggs1  Montserrat Cases3  David J. Heard2  Manuel Pastor3  François Pognan2  Ferran Sanz3  Christof H. Schwab5  Thomas Steger-Hartmann4  Andreas Sutter4  David K. Watson1  | |
[1] Lhasa Ltd., 22-23 Blenheim Terrace, Woodhouse Lane, Leeds, LS2 9HD, UK; E-Mails:;Department of Preclinical Safety, Novartis Institutes for Biomedical Research (NIBR), Postfach CH-4002, Basel, Switzerland; E-Mail:;Research Programme on Biomedical Informatics (GRIB), Fundació IMIM, Universitat Pompeu Fabra, PRBB, Dr. Aiguader 88, 08003 Barcelona, Spain; E-Mails:;Bayer HealthCare, Investigational Toxicology, Müllerstr. 178, 13353 Berlin, Germany; E-Mails:;Molecular Networks GmbH, IZMP, Henkestr. 91, 91052 Erlangen, Germany; E-Mail: | |
关键词:
predictive toxicology;
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DOI : 10.3390/ijms13033820 | |
来源: mdpi | |
【 摘 要 】
There is a widespread awareness that the wealth of preclinical toxicity data that the pharmaceutical industry has generated in recent decades is not exploited as efficiently as it could be. Enhanced data availability for compound comparison (“read-across”), or for data mining to build predictive tools, should lead to a more efficient drug development process and contribute to the reduction of animal use (3Rs principle). In order to achieve these goals, a consortium approach, grouping numbers of relevant partners, is required. The eTOX (“electronic toxicity”) consortium represents such a project and is a public-private partnership within the framework of the European Innovative Medicines Initiative (IMI). The project aims at the development of
【 授权许可】
CC BY
© 2012 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.
【 预 览 】
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RO202003190045216ZK.pdf | 1050KB | download |