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SciBite / Knowledge Hub / Resources / Datasets for drug discovery [Use Case]

Datasets for drug discovery [Use Case]

Elsevier understands the challenges of drug discovery. Our comprehensive, high-quality and machine-readable datasets provide clear data provenance and support evidence-based decisions. Through our vast history of supporting the life sciences, we can provide:
  • Curated datasets from full-text articles in disciplines across life sciences, including medicine, chemistry, biochemistry, genetics, immunology, microbiology, pharmacology, toxicology and more.
  • FAIR data in 11 therapy areas
  • Specialized data, such as bioactivity data, biological relationships, substances, reactions and more

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.
  • Inform virtual screening
  • Reveal promising drug targets
  • Improve biomarker identification and prioritization
  • Assess the current treatment landscape for a disease
  • Make go/no-go decisions using predictive chemistry

Featuring high-impact research from prestigious journals such as Cell Press and Lancet, the dataset includes biological relationships, small molecule interactions, and clinical trial data. These datasets enable informed decision-making in predictive chemistry, driving efficiency and innovation in drug discovery processes. Learn more at elsevier.com/solutions/datasets.
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