title: Global analysis of publicly available safety data for 9,801 substances registered under REACH from 2008-2014.
abstract: The European Chemicals Agency (ECHA) warehouses the largest public dataset of in vivo and in vitro toxicity tests. In December 2014 this data was converted into a structured, machine readable and searchable database using natural language processing. It contains data for 9,801 unique substances, 3,609 unique study descriptions and 816,048 study documents. This allows exploring toxicological data on a scale far larger than previously possible.
  Substance similarity analysis was used to determine clustering of substances for hazards by mapping to PubChem. Similarity was measured using PubChem 2D conformational substructure fingerprints, which were compared via the Tanimoto metric. Following K-Core filtration, the Blondel et al. (2008) module recognition algorithm was used to identify chemical modules showing clusters of substances in use within the chemical universe.
  The Global Harmonized System of Classification and Labelling provides a valuable information source for hazard analysis. The most prevalent hazards are H317 “May cause an allergic skin reaction” with 20% and H318 “Causes serious eye damage” with 17% positive substances. Such prevalences obtained for all hazards here are key for the design of integrated testing strategies. The data allowed estimation of animal use.
  The database covers about 20% of substances in the high-throughput biological assay database Tox21 (1,737 substances) and has a 917 substance overlap with the Comparative Toxicogenomics Database (~7% of CTD). The biological data available in these datasets combined with ECHA in vivo endpoints have enormous modeling potential. A case is made that REACH should systematically open regulatory data for research purposes.
authors: Center for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health, Environmental Health Sciences, Baltimore, MD, USA.
authors: Thomas
authors: T
authors: Luechtefeld
authors: Center for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health, Environmental Health Sciences, Baltimore, MD, USA.
authors: Alexandra
authors: A
authors: Maertens
authors: The Rutgers Center for Computational & Integrative Biology, Rutgers University at Camden, NJ, USA.
authors: Daniel P
authors: DP
authors: Russo
authors: CAAT-Europe, University of Konstanz, Konstanz, Germany.
authors: Costanza
authors: C
authors: Rovida
authors: The Rutgers Center for Computational & Integrative Biology, Rutgers University at Camden, NJ, USA.|Department of Chemistry, Rutgers University at Camden, NJ, USA.
authors: Hao
authors: H
authors: Zhu
authors: Center for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health, Environmental Health Sciences, Baltimore, MD, USA.|CAAT-Europe, University of Konstanz, Konstanz, Germany.
authors: Thomas
authors: T
authors: Hartung
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions; D005060:Europe; D015386:Hazardous Substances / Q000633:toxicity*; D033181:Information Dissemination / Q000379:methods*; D018570:Risk Assessment; D012984:Software; D014116:Toxicology / Q000379:methods
chemical_list: D015386:Hazardous Substances
keywords: animal testing; chemical toxicity; computational toxicology; database; in silico