There have been some very interesting disruptive technologies emerging in the last couple of years that are dramatically changing the way massive amounts of structured and unstructured molecular and medical information are managed. This new technology is popularly referred to as “Big Data.” At the same time, experts are beginning to refer to the new world of “personalized” medicine as “precision” medicine. The term "precision" medicine may be far more apt, as these new therapies will to a great extent be made possible by Big Data. How will Big Data and Precision Medicine change biobanking?
Precision medicine, as defined by the National Research Council1, is based on new discoveries in molecular biology that is integrated, at the point of care, with clinical data to design treatments that are customized to the needs of individual patients. This is the new holy grail of bioinformatics.
Until recently, treatment for most medical conditions was necessarily a one-size-fits-all approach, because data/information on the disease processes occurring at an individual patient’s molecular level was simply not available. However, from the time biospecimens have been collected, stored, and analyzed, and especially after the human genome was first sequenced, scientists have been gaining a far better understanding of the health and medical needs of patients, based on their individual genetic blueprint. The ability to sequence an individual’s genome at a lower cost has also spurred the growth of bioinformatics and systems biology, and led to the accumulation of vast amounts of data. This superabundance of data and the difficulties in sharing and using it has been well discussed over the past few years.
What the medical research community and the biobanking organizations that support this community may not fully realize is the extent of the paradigm shift that is immediately ahead. How will Big Data change the existing structure of biobanks, which have primarily remained at the periphery of the research community?
The Big Data techniques and associated technology will enable a macroscopic view of health, including the ability to recognize patterns or clues to disease genesis and development at a molecular level. Researchers will be able to collectively leverage a variety of scientific data stores, i.e. genomics, proteomics, metabolomics, lipidomics, etc., to tease out patterns and associations. Rather than examining data from just one of these platforms as in the past, scientists will be able to look at multiple platforms, resulting in a more precise understanding of disease processes and potential new solutions for diagnosis and intervention. Profiling a person’s proteome or metabolome can help clinicians see global changes in the body far in advance of symptoms.
The majority of this data will come from biospecimens. The question then becomes, where will the data be stored and how will it be linked to the specimen, the patient, the clinical outcome, and made accessible to investigators? The current structure, with its silos and barriers, is about to go away: Big Data will ultimately require biobanks to more actively participate in the virtual research environment.
Displayed to the right: Infographic courtesy of NetApp
Those of us in the Information Technology industry have been on this paradigm shift roller coaster for years. However, this dramatic change is about to knock on the door of the brick-and-mortar facilities that house the biospecimens needed for cutting edge research. This is going to have a profound impact on the world of biobanks, and the medical industry as a whole.
I have been thrilled to participate in several of our mega cohort studies and biobanking projects, such as, Morris Animal Foundation, National Children's Study, and City of Hope. Specifically, in the City of Hope project, the California Teacher's Study uses mobile devices and cloud-based technology to cut the time and cost of managing huge amounts of data. This is a great example of the type of change that is occurring from the point of collection through the receipt of the sample. Fisher BioServices collects and manages approximately 170,000,000 million samples from patients and healthy controls are at the vortex of precision medicine. And as part of the ecosystem that supports a wide variety of studies, we are very serious about our pivotal role in helping to determine disease etiology, develop new therapies, and advance public health, and are actively working to become an access point for Big Data, as well as a provider of biobanking services. If you are interested in more information about these projects, please click on the following link to download our eBooks: Biobanking for Animal Health: Morris Animal Foundation is Taking Veterinary Research to a New Level and Next Generation Cohort Studies and Biobanking: How Cloud Technology is Accelerating Translational Research.
I believe that the next generation of bioinformatics in biobanking, as with medical research, is all about “Big Data” and will dramatically shift the way the metadata associated with a sample is collected, stored, and leveraged. Biobanks will soon play a more central role in medical research and the growth of precision medicine.
1Toward Precision Medicine. Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease. National Research Council, National Academies Press, Washington D.C., 2011, www.nap.edu