I was in Silicon Valley last week for the seventh annual Personalized Medicine World Conference, and all the buzz was around clinical applications for NGS. While there have clearly been significant advances in the field, it is also clear that we are a long way off from NGS becoming a routine part of clinical care.

Several trends emerged after listening to the host of esteemed presenters:

– Phenotypes are desperately needed. The ability to make statistically-driven interpretations of genetic variations is confounded by the lack of numbers behind most variations. David Haussler from UCSC characterized the scope of the problem well when he stated that “at the molecular level, every disease is a rare disease.” This statement really underscores just how large the numbers need to be before interpretation can consistently rely on established patterns.

– Interpretation is the bottleneck. Based on the above, it is not surprising to hear that interpretation is currently the biggest cost in clinical use of NGS. According to Michael Snyder from Stanford, it takes an average of 200 person hours to interpret a single genome, with a cost of over $20,000. The problem is compounded by the number of variants of truly unknown significance, each of which can take days to research.

– Everyone is trying to bring their own solution to the problem, creating what Haussler called a “forest of unconnected silos.” Indeed, many of the presentations were by program directors at different institutions describing their new genome database. With the emphasis needing to be on sheer numbers to power statistically-driven interpretation, connecting these silos is a critical task. An initiative co-founded by Haussler, the Global Alliance for Genomics & Health, is seeking to establish standards that will enable such connectivity.

– The need for databases extends to the regulatory side as well. Margaret Hamburg from FDA made the point that the Agency needs help “developing and curating databases dynamically,” to enable faster approval of sequencing tests. Hamburg recently stated that databases were used to speed approval of Illumina’s recent NGS tests for cystic fibrosis, and it will be interesting to learn which databases FDA relies upon in this context.