IDBS Blog | 26th September 2014

Bringing Genomics to the Bedside

With the right time, the right data analytics and the right expertize, bringing genomics to the bedside can become a reality. The ambition and vision is there, but major challenges still lie ahead. What needs to happen in genomic medicine for the exceptional cases to become the norm?

Data, data, data

Information sharing should be guided by organizational policy. It is time to move away from a disordered landscape of data, towards the widespread gathering and sharing of good quality, standardized clinical data. More robust, accessible analysis in the context of disease is also needed. It will be vital to bridge the gap between information generated by high throughput sequencing technologies and the wealth of disease-related information that is available.

New diagnostics

Diagnostic companies and Clinical Laboratory Improvement Amendments (CLIA) laboratories will increasingly use high throughput data to design new diagnostics. Celera – a subsidiary of Quest Diagnostics, for instance, is implementing a platform that enables deep sequencing analytics. This will enable it to develop meaningful new therapies that improve human health.

Public-private collaboration

Initiatives like eTRIKS will help usher in the standardization of research. Standards must be used to support reproducible research, which can in turn validate a study in the context of another. Researchers should also seek to standardize the way samples are collected and processed. This will help reduce the amount of experimental variation.

Prospective power

A recent Accenture blog highlighted how standardized, accessible data could bring about a new era of personalized medicine and better outcomes for patients. One new program across Quebec will put this into action, collecting information about patients with many types of cancer and creating a large biobank. Run by the Segal Cancer Centre at the Jewish General Hospital, the program will enable treatments to be targeted to match specific proteins and improve patient outcomes.

When it comes to omics data management, analysis and action, we are on the right path. Making the necessary data available to the right people at the right time will be key. Clinical practice must move towards longitudinal studies that give future researchers a legacy of strong clinical data and samples. Those who collaborate more effectively with patients, technology and regulators will really drive success using genomics in the clinic.

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