Case Study: Uppsala University identifies COVID-19 drug candidates with KNIME

How KNIME helps identify new drug candidates for COVID-19

Uppsala University used KNIME to accelerate drug repurposing research during the COVID-19 pandemic. Faced with the challenge of combining large, heterogeneous life sciences datasets and analyzing complex small-molecule information for new drug candidates, the university needed a scalable, automated, and reproducible way to support its drug discovery pipeline.

Using the KNIME Analytics Platform and predictive AI workflows, the team automated data retrieval from public chemical databases, standardized molecular structures, and performed substructure searches and clustering to identify promising compounds. The result was the discovery of 7,836 compounds from DrugBank and 36,521 from the CAS dataset, with 135 overlapping hits—including remdesivir, fludarabine, and darunavir—several of which advanced into clinical trials; KNIME helped Uppsala University deliver this process efficiently and reproducibly.

Uppsala University