As we experience the digitalization of our own lives, one thing is clear: We are drowning in data. At times, we are hard pressed to get the information needed from that data, let alone build any sort of informed action plan based on that information. This is no less true for all participants in the Healthcare ecosystem. That ecosystem consists of providers, payors, Pharmaceutical and Biotechnology companies, and the patients and clinical participants that make the moving parts of that ecosystem.
The purpose of a functioning ecosystem is to support all those that exist in it, depend upon it, and perpetuate the health of said ecosystem. Healthcare is supposed to maintain health, and healthy outcomes of people and populations. However, to do that, the life sciences industry needs to be capable of generating and successfully bringing to market products that support the therapeutic treatment and prevention of disease. There are massive data stores that must be managed for that to happen.
Successfully managing that data benefits not only the discovery, development, and approval of new drugs for treatment, but it will have the added benefit of driving down the cost of delivering and managing healthcare. Since 2004, there has been an almost 10,000-fold reduction in the cost of sequencing a human genome. With genomic sequencing approaching the $1,000 cost mark, it is likely that we will soon see it become as in-patient an exercise as having an x-ray performed. At roughly 2Gbyte per sequence, this will increase the storage needs of clinics, but also provide a utility opportunity for the ecosystem.
There are an increasing number of drugs on that have genomic biomarkers as part of their labeling. By successfully pairing drug treatments to the pathology they are supposed to treat, through identification of genomic biomarkers, we can increase the likelihood of therapeutic success, and therefore realize the ROI that any payor organization involved gets by supporting, through reimbursement, the usage of that drug.
For the life sciences companies themselves, through partnerships with provider and payor organizations, harnessing the massive amounts of data around patient populations, as well as the data that they themselves are amassing through their own research and development, would not only increase their likelihood of investing in the right development direction, but also speed their time to market through the successful identification of clinical participants. Faster time to market means more treatment options for both payor and providers.
And genomics is only part of the problem. The field of Connectomics maps neural connections and pathways of the brain, and relies on nanometer resolution electron microscopy to visualize these connections. The largest data sets are now in the 100-terabyte range. Data sets are expected soon to reach petabyte scales largely driven by faster, higher-resolution electron microscopes. Detectors and imaging facilities coming on the market in the next three to five years are expected to produce data in excess of one terabyte per second!