The Knowledge Connector decision support system for multiomics-based precision oncology

Comprehensive Summary

This study describes the development and implementation of the Knowledge Connector (KC), a clinical decision support system designed to assist molecular tumor boards in precision oncology. The KC integrates individual patients’ molecular and clinical data with real world knowledge to support biomarker annotation and treatment recommendation. It helps with the structured analysis of complex molecular profiles, including data from whole-genome sequencing, whole-exome sequencing, RNA sequencing, and other techniques. One feature of the KC is the use of blocks of clinical knowledge (BoCKs), which link specific biomarkers to diagnostic and other clinical evidence. By combining information from multiple knowledge bases into one interface, the KC supports informed clinical decision making and MTB recommendations.

Outcomes and Implications

Results with the KC showed that it improves data curation efficiency and supports the interpretation of complex biomarkers such as homologous recombination. The platform facilitates the identification of treatment options and clinical trials. The use and growth of the BoCKbase demonstrated how curated knowledge can be shared across institutions and over time. Overall, the study shows that the Knowledge Connector is a helpful tool that supports medical decision-making in molecular tumor boards and helps enable the scalability of precision cancer medicine.