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An open source statistical web application for validation and analysis of virtual cohorts.

Christian Ohmann1, Takoua Khorchani2, Alexandru Cracanel3

  • 1European Clinical Research Infrastructures Network (ECRIN), Kaiserswerther, Strasse 70, 40477, Düsseldorf, Germany. christianohmann@outlook.de.

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Summary

The SIMCor project developed an open-access web tool to analyze virtual cohorts for in-silico trials, addressing a gap in statistical analysis methods for medical research efficiency.

Keywords:
In-silico trialSIMCorShinyValidationVirtual cohortWeb application

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Area of Science:

  • Medical Research
  • Computational Biology
  • Biostatistics

Background:

  • Conventional medical research involves pre-clinical studies, animal testing, and human clinical trials.
  • In-silico trials and virtual cohorts offer potential to enhance clinical research efficiency but face challenges.
  • A key challenge is the lack of accessible statistical tools for analyzing virtual cohorts and in-silico trials.

Purpose of the Study:

  • To develop a user-friendly, open-access web application for validating virtual cohorts.
  • To provide an R-statistical environment specifically designed for in-silico trial analysis.
  • To facilitate the comparison of virtual cohorts with real-world datasets.

Main Methods:

  • Development of a web application within the EU-Horizon funded SIMCor project.
  • Implementation of an R-statistical environment for cohort validation and in-silico trial application.
  • Integration of existing statistical techniques for virtual cohort comparison.

Main Results:

  • A functional, open-access, menu-driven web tool (SIMCor) has been developed and validated.
  • The tool supports the validation of virtual cohorts against real datasets.
  • User guidance and help features are integrated into the application.

Conclusions:

  • The SIMCor tool addresses the need for accessible statistical analysis in in-silico trials.
  • The application provides a practical platform for validating and utilizing virtual cohorts.
  • Future work includes expanding the tool's application to diverse research domains and enhancing its functionality.