Why Hasn't Clinical Genetics Taken Off? (part 2)

Sultan Meghji

In my previous post, I made the broad comment that education of the patient and front line doctors was the single largest barrier to entry for clinical genetics. Here I look at the steps in the scientific process and where the biggest opportunities lie:

The Sequencing (still)

PCR is a perfectly reasonable technology for sequencing in the research lab today, but the current configuration of technologies need to change. We need to move away from an expert level skill set and a complicated chemistry process in the lab to a disposable, consumer friendly set of technologies. I’m not convinced PCR is the right technology for that and would love to see nanopore be a serious contender, but lack of funding for a broad spectrum of both physics-only as well as physical-electrical startups have slowed the progress of these technologies. And waiting in the wings, other technologies are spinning up in research labs around the world. Price is no longer a serious problem in the space - reliable, repeatable, easy to use sequencing technologies are. The complexity of the current technology (both in terms of sample preparation and machine operation) is a big hurdle.

The Analysis (compute)

Over the last few years, quite a bit of commentary and effort has been put into making the case that the compute is a significant challenge (including more than a few comments by yours truly in that vein!). Today, it can be said with total confidence that compute is NOT a problem. Compute has been commoditized. Through excellent new software to advanced platforms and new hardware, it is a trivial exercise to do the analysis and costs tiny amounts of money ($<25 per sample on a cloud provider appears to be the going rate for a clinical exome in terms of platform & infrastructure cost). Integration with the sequencer and downstream medical middleware is the biggest opportunity.

The Analysis (value)

The bigger challenge on the analysis is the specific things being analyzed as mapped to the needs of the patient. We are still in a world where the vast majority of the sequencing work is being done in support of a specific patient with a specific disease. There isn’t even broad consensus yet in the scientific community about the basics of the pipeline. A movement away from the recent trend in studying specific indications (esp. cancer) is called for. Broadening the sample population will allow us to pick simpler, clearer and easier pipelines which will then make them more adoptable. It would be a massive benefit to the world if the scientific, medical and regulatory communities would get together and start creating, in a crowdsourced manner, a small number of databases that are specifically useful to healthy people. Targeting things like nutrition, athletics, metabolism, and other normal aspects of daily life. A dataset that could, when any one person’s DNA is references, would find something useful. Including the regulators is key so that we can begin to move away from the old fashioned model of clearances that still permeate the industry.

The Regulators

Beyond the broader issues around education I referenced in my previous post, there is a massive upgrade in the regulation infrastructure that is needed. We still live in a world of fax machines, overnight shipping of paper documents and personal relationships all being more important than the quality of the science you as an innovator are bringing to bear.

Consider the recent massive growth in wearables, fitness trackers and other instrumentation local to the human body. Why must we treat clinical genetics simply as a diagnostic and not, as it should be, as a fundamental set of quantitative data about your body that you can leverage in a myriad of ways. Direct to consumer (DTC) genetics companies, most notably 23andme, have approached this problem poorly - instead of making it valuable to the average consumer, what they’ve done is attempted to straddle the line between medical and not. The Fitbit model has shown very clearly that lifestyle activities can be directly harnessed to build commercial value in scaling health related activities without becoming a regulatory issue. It’s time for genetics to do the same thing.

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