Researchers at the National Center for Supercomputing Applications (NCSA), Mayo Clinic and the Genomic Institute of Singapore have begun a pilot project to develop an effective way to visually present genomic data to clinicians. The project is one of several being carried out by the Mayo Illinois Alliance for Technology-Based Healthcare, a joint effort launched in 2010.
Biomedical researchers generate a tremendous amount of genomic data about cancer, which has the potential to improve clinicians' ability to diagnose, treat and prevent the disease. But in order for this complex, heterogeneous data to be useful in a clinical setting, it must be clear and easy to understand, with the relevant information drawn from the overwhelming flood.
‘There are all sorts of ways in which visualisation tools could be deployed to inform students, clinical practitioners, genetic counsellors and patients about the role of genomics in health and disease,’ said Dr Frank Prendergast, director of Mayo's Center for Individualised Medicine and a co-principal investigator for the pilot project. ‘I am especially taken with how such tools can be used to explain genomics to patients; gene sequences by themselves can be stultifyingly uninformative!’
The goal of the project is to ‘bridge the gap between research and clinicians,’ added Michael Welge, who leads the data-intensive technologies and applications research team at NCSA. ‘How do you visually represent information from the research laboratory to the clinician so the clinician can use this in their workflow?’
Welge's team brings substantial data visualisation expertise to the project, while the team from Singapore provides insight into the research perspective on the data and how it is currently visually represented. The clinicians from Mayo and other hospitals (including Carle Hospital in Urbana) can explain their typical workflow and how they could use genomic data in diagnosis and in formulating treatment plans.
The plan is to have an initial prototype or mock-up early 2011, which will be used as the basis for follow-on proposals and research. Welge believes a system could be ready for clinical deployment in two to five years.