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

Nature Reviews Drug Discovery

Volumn 16, Issue 12, 2017, Pages 811-812

  Sanz, Ferran ^a   Pognan, François ^b   Steger Hartmann, Thomas ^c   Díaz, Carlos ^d  

^a UNIVERSITAT POMPEU FABRA   (Spain)

^b NOVARTIS PHARMA AG   (Switzerland)

^c BAYER AG   (Germany)

^d Synapse Research Management Partners   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

DATA BASE; DRUG APPROVAL; DRUG INDUSTRY; DRUG INFORMATION; DRUG SAFETY; ETOX DATABASE; FOOD AND DRUG ADMINISTRATION; INCIDENCE; INFORMATION DISSEMINATION; LIVER TOXICITY; MEDICAL DOCUMENTATION; PRACTICE GUIDELINE; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REVIEW; SOFTWARE; STANDARDIZATION; STATISTICAL MODEL; ADVERSE DRUG REACTION; HUMAN; PRECLINICAL STUDY; PROCEDURES; RISK ASSESSMENT;

DRUG EVALUATION, PRECLINICAL; DRUG INDUSTRY; DRUG-RELATED SIDE EFFECTS AND ADVERSE REACTIONS; HUMANS; INFORMATION DISSEMINATION; RISK ASSESSMENT;

EID: 85035327690     PISSN: 14741776     EISSN: 14741784     Source Type: Journal    
DOI: 10.1038/nrd.2017.177     Document Type: Review

References (5)

1. Obiol-Pardo, C. et al. A multiscale simulation system for the prediction of drug-induced cardiotoxicity. J. Chem. Inf. Model. 51, 483-492 (2011).
2. Carbonell, P. et al. Hepatotoxicity prediction by systems biology modeling of disturbed metabolic pathways using gene expression data. ALTEX 34, 219-234 (2017).
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).
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).