Silvi was founded in 2018 by Professor in Health Economic Evidence, Tove Holm-Larsen. The idea for Silvi stemmed from Holm-Larsen’s own research, and the need to conduct meta-analyses faster.
Originally, the ideas behind Silvi were a component of a larger project. In 2016, Professor Holm-Larsen founded the group “Evidensbaseret Medicin 2.0” in collaboration with researchers from Ghent University, Technical University of Denmark, University of Copenhagen, and other experts. The goal of EBM 2.0 was to answer the question:
“How do we optimize evidence-based medicine to its highest potential using Big Data and Artificial Intelligence?”
The group wanted to build a comprehensive system using knowledge of pharma, technology, and AI to improve Real World Evidence collection and analysis to ensure that all patients are being treated to the best of current knowledge. The project gained traction, and it was among the finalists for the Grand Solution fund by Innovationsfonden in 2018.
In the final round of interviews, EBM 2.0’s funding application got rejected. However, they received the following piece of advice: Divide the project into smaller entities.
This is exactly what Holm-Larsen did. Silvi.ai was created.
Silvi uses AI to increase the speed of collecting and analyzing published data to created meta-analyses. When using Silvi, the researcher still makes all the scientific decisions, but with AI extracted data the speed of doing meta-analysis increases immensely. Furthermore, the meta-analyses are connected to literature databases to ensure that the results are always up to date.