The effective utilization of large gene panel molecular diagnostic tests such as the UCSF 500 in the clinic depends on integration of data from many sources (clinical data from APeX, Phase I program data, genetic variant knowledge, drug response data) and expertise from many groups (genome scientists, pathologists, oncologists, genetic counselors).
Toward this end, the Molecular Oncology Initiative is working to collaborate with research groups at UCSF who are taking big data approaches to tackle precision oncology research questions.
By facilitating the integration of data generated at the bench with data utilized in clinical decision support, and enabling basic researchers to interrogate molecular oncology databases with cutting edge computational approaches, the Molecular Oncology Initiative will continue to move forward on its goals to:
- Continually iterate on knowledge about clinical actionability of genomic findings identified by molecular diagnostic tests such as the UCSF 500
- Develop evidence-based roadmaps for optimal molecular diagnostic test utilization
- Support the development of “basket trials”
- Optimize algorithms to streamline and improve clinical decision making
- Tap in to external precision oncology networks to improve patient outcomes