One the the big challenges to successfully commercializing the advances in genomic research for the medical device industry is how to present the information in a form that will be useful to clinician. Historically the vast majority of physicians practicing today were taught microbiology, biochemistry and physiology in medical school. In day to day practice they use their knowledge to augment their clinical diagnostic and treatment methods. However, the vast majority of clinicians did not learn about gene expression and the depth of detail it is helping bring to systems biology. Moreover, it will be very difficult to get much more than an appreciation of the insights this information will bring to medicine even when it becomes part of the medical school curriculum. As a result there will be a need to have technology that will help the clinician interpret the tremendous volume of information a genomic expression profile gives.
A first step toward such a tool has been developed by Gabriel Eichler, Ying Feng, Yuchun Guo and Sui Huang in the Ingber laboratory at the Children’s Hospital and Harvard Medical School, Boston. The Gene Expression Dynamics Inspector (GEDI) approach uses color patterns related to gene expression results to convey the gene expression “state” of a patient. The concept relies heavily on the doctor’s ability to detect visual patterns and correlate them with the other tools at their disposal to create a diagnosis. From the product development point of view its clear that the creators of this software understood their customer and developed a tool that would be within their capabilities to use. The technology is available to the public without charge.
The attempt to create this type of tool highlights the need and the challenges that the medical industry and its engineers will face to create products that simplify the interpretation of the volume of data made available by genomic techniques and make them useful to the clinician.
Here is a more traditional approach for reporting clinical data as a result SNP genetic testing of a patient to a clinician.
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