Most of the data in published clinical trials is unstructured. Molecular Connections’ curation experts help you extract valuable associations out of the unstructured clinical trial data, to enhance trial design and output. We also provide domain expertise across multiple therapeutic areas and several indications. The proprietary text mining engine helps you identify drug combinations in trials and also perform comparative effectiveness research.
Clinical trials have become the corner stone of evidence-based precision medicine. Published clinical trial data contain important information on the trial design and site selection. Most of the information in these clinical trial databases are stored in the form of unstructured text. Molecular Connections’ text mining expertise is useful in extracting relationships from this unstructured text. We perform systemic review of clinical trial data and meta-analysis to extract important drug characteristics such as safety and efficacy of drugs in comparison to other competitors’ drugs.
Molecular Connections’ curation helps the pharmaceutical companies in different areas including:
  • Trial design
  • Clinical trial site/ KOL identification
  • Adverse event extraction
  • Systemic review and Meta analysis
  • Drug/ drug combination extraction
  • Comparative effectiveness research

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Mining clinical trials by combining automated and manual curation
This case study outlines two independent investigations using the clinical trial data to provide information for the clinical trial decision makers – the first identifies all the late stage combinatorial therapies within the therapeutic space of NSCLC and the second identifies the comparator drugs in the late stage trials.

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