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SciBite / Knowledge Hub / Resources / Datasets for pre-clinical and clinical R&D [Use Case]

Datasets for pre-clinical and clinical R&D [Use Case]

Elsevier understands the challenges of pre-clinical and clinical R&D. Our comprehensive, high-quality and machine-readable datasets provide clear data provenance and support evidence-based decisions. The “Datasets for Pre-Clinical and Clinical R&D” provides a rich collection of machine-readable data to support various facets of drug research and development. Through our vast history of supporting the life sciences, we can provide:
  • Build and train models for predictive toxicology applications
  • Computing animal-human model concordance
  • Build and train various QSAR models
  • Predictive modeling for clinical outcomes
  • Designing effective synthesis scale-up routes

With trusted data from 24 major disciplines, including biochemistry, genetics, chemistry, pharmacology, and toxicology, this resource supports virtual screening, drug target identification, biomarker prioritization, and treatment landscape assessment.
  • Structured biomedical literature from 8,300 journals (including 3,300 not found in Medline)
  • 5.1 million conference abstracts from 11,500 conferences
  • Chemistry data with 23 million single-step reactions and 9 million substances with bioactivities
  • Drug safety data extracted from FDA and EMA regulatory documents
  • Complete dataset access via API

This comprehensive data access supports evidence-based decision-making and enhances the efficiency of pre-clinical and clinical R&D efforts. Learn more at elsevier.com/solutions/datasets.
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