A participant pointed out that FDA, CLIA, the courts, and the court of public approval will all factor into this new era of disease-gene association and that there will be liability issues to address. He offered the innovative biotechnology industry as an analogy. A biotechnology company is supported by investors and dependent on the public buying its product. If the company gets it wrong (e.g., produces a faulty product that causes harms or does not work), its board will vote to close the company down because it failed and is not making money. Checks and balances also occur out in the marketplace where consumers vote with their dollars. The participant said that it is fine to be ahead of the field, whether in biotechnology or in genomic testing, but one should keep in mind that he will be held accountable by investors and consumers, by regulators, and by the courts.

The Evolution of Technology and Data

A participant suggested that the era of SNPs is dead since they provide such a small amount of information and that we are quickly moving to full genomic sequencing. The participant asked whether it is even worthwhile to continue discussing how to use SNPs. Marc Williams responded that the fundamental issues are more concerned with managing the information than with any specific technology. Making things clinically relevant is not dependent on whatever the technology currently being used is but rather on the level of confidence there is in the technology’s predictive value and if that information is actionable.

This is one of the challenges, Blumberg added, when traditional methods of evidence generation are so much slower than the advance of technology and technological methodology. Perhaps by the time that the current warfarin clinical studies produce results in 2012, another gene may have been identified that, when added to the protocol, makes the difference between clinical utility and nonclinical utility. The old method of one test at a time, one protocol at a time, one disease at a time, is at odds with the profusion of new data and technology that is now available.

Vanier said that this is an evolving process. The algorithms and infrastructure it takes to translate SNP information into an end use are not unlike those that would be used for targeted sequencing and which could then be adapted to whole genome sequencing. The obvious difference is the volume of data that will be put through that infrastructure. SNPs are a first step toward mass utility whole genome sequencing, he said.

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