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

The conventional approach to developing medical treatments and medical devices usually covers pre-clinical and in-vitro investigations, in-vivo animal studies and clinical trials with humans. In-silico trials and virtual cohorts present a promising avenue for addressing the challenges inherent in clinical research and improving its efficiency. Despite considerable advancements in the field of in-silico trials, several notable gaps and challenges still need to be addressed, one is the limited availability of open and user-friendly statistical tools to support the specific analysis of virtual cohorts and in-silico trials. In the EU-Horizon funded project SIMCor we have developed a web application, providing a R-statistical environment supporting the validation of virtual cohorts and the application of validated cohorts for in-silico trials. It provides a practical platform for validating cohorts and has implemented existing statistical techniques that can be applied to compare virtual cohorts with real datasets. It is fully open, generic and menu driven and provides user guidance and help ( https://github.com/ecrin-github/SIMCor , https://zenodo.org/records/14718597 ).The tool has been developed according to specified user requirements and has been extensively tested and validated. Important next steps are to gain more experience with the tool in other domains and research environments and to extend its functionality.

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Publication Details

Journal
Scientific Reports
Published
2025-05-06
DOI
https://doi.org/10.1038/s41598-025-99720-3
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Jan Brüning, Christian Ohmann, Pablo Emilio Verde, Takoua Khorchani et al.
1 links
Scientific Reports
Scientific Computing and Data Management
article

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

Jan Brüning, Christian Ohmann, Pablo Emilio Verde, Takoua Khorchani, Alexandru Cracanel
article en

Abstract

The conventional approach to developing medical treatments and medical devices usually covers pre-clinical and in-vitro investigations, in-vivo animal studies and clinical trials with humans. In-silico trials and virtual cohorts present a promising avenue for addressing the challenges inherent in clinical research and improving its efficiency. Despite considerable advancements in the field of in-silico trials, several notable gaps and challenges still need to be addressed, one is the limited availability of open and user-friendly statistical tools to support the specific analysis of virtual cohorts and in-silico trials. In the EU-Horizon funded project SIMCor we have developed a web application, providing a R-statistical environment supporting the validation of virtual cohorts and the application of validated cohorts for in-silico trials. It provides a practical platform for validating cohorts and has implemented existing statistical techniques that can be applied to compare virtual cohorts with real datasets. It is fully open, generic and menu driven and provides user guidance and help ( https://github.com/ecrin-github/SIMCor , https://zenodo.org/records/14718597 ).The tool has been developed according to specified user requirements and has been extensively tested and validated. Important next steps are to gain more experience with the tool in other domains and research environments and to extend its functionality.

Scientific ReportsVol. 15(1)
Transylvania University of Brașov (RO), European Clinical Research Infrastructure Network (FR), Heinrich Heine University Düsseldorf (DE), Charité - Universitätsmedizin Berlin (DE)
European Commission, Technische Universiteit Eindhoven, Horizon 2020 Framework Programme
Industry, innovation and infrastructure
Openalex Percentile: Top 90%
Scientific Computing and Data Management
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