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Value of shared preclinical safety studies - The eTOX database.

Katharine Briggs1, Chris Barber1, Montserrat Cases2

  • 1Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds LS11 5PS, United Kingdom.

Toxicology Reports
|October 1, 2017
PubMed
Summary

This study analyzed preclinical safety data from 1214 small molecule drugs. The findings support using this shared data to build in silico predictive models for drug development and toxicity assessment.

Keywords:
ALP, alkaline phosphataseALT, alanine aminotransferaseAST, aspartate aminotransferaseBiomarkersCDISC, Clinical Data Interchange Standards ConsortiumCRO, contract research organisationDILI, drug induced liver injuryData miningData sharingEFPIA, European Federation of Pharmaceutical Industries and AssociationsFN, false negativeFP, false positiveGLP, good laboratory practiceICH, International Conference on HarmonisationIMI, Innovative Medicines InitiativeINHAND, International Harmonization of Nomenclature and Diagnostic CriteriaIT, information technologyMCC, Matthews correlation coefficientOECD, Organisation for Economic Co-operation and DevelopmentOntologyPDF, Portable Document FormatPDF/A, ISO-standardized version of PDF specialized for the digital preservation of electronic documents.QA, quality assuranceSEND, Standard for Exchange of Nonclinical DataSME, small-to-medium enterpriseTN, true negativeTP, true positiveToxicologyULN, upper limit of normaleTOX, integrating bioinformatics and chemoinformatics approaches for the development of expert systems allowing the in silico prediction of toxicities

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Area of Science:

  • Pharmacology and Toxicology
  • Computational Chemistry
  • Drug Safety

Background:

  • Preclinical safety data is crucial for drug development.
  • Sharing data across pharmaceutical companies can enhance safety assessments.
  • The eTOX project aims to consolidate and analyze such data.

Purpose of the Study:

  • To analyze a large database of preclinical safety data for small molecule drugs.
  • To assess the feasibility of building in silico predictive models using this data.
  • To evaluate the utility of the data for understanding treatment-related effects and toxicity biomarkers.

Main Methods:

  • Analysis of a database containing 3970 reports from 13 pharmaceutical companies.
  • Examination of species, duration of exposure, and administration route for data homogeneity.
  • Utilizing the eTOX ontology to categorize clinical chemistry and histopathology findings.
  • Mining data to assess the sensitivity of in vivo biomarkers for liver toxicity.

Main Results:

  • A comprehensive analysis of preclinical safety data for 1214 small molecule drugs and candidates.
  • Identified common treatment-related clinical chemistry and histopathology findings.
  • Evaluated the potential for creating robust in silico predictive models.
  • Assessed the sensitivity of established in vivo biomarkers for liver toxicity risk.

Conclusions:

  • The shared preclinical safety database is valuable for in silico model development.
  • The data can inform early drug development and toxicity risk assessment.
  • Further analysis can enhance predictive toxicology and drug safety evaluations.