- Human Biospecimens
- For Researchers
- For Biospecimen Contributors
- For Patients
December 9, 2014
As technology grows more advanced, researchers have an easier time analyzing various molecular codes: DNA, RNA, proteomes, and other biomarkers. Using advanced technology, scientists can more swiftly pinpoint which genes are relevant to various physiological functions, which genes regulate the actions of others, and which genes are typically spliced out before protein expression.
One potential complication of these innovations, however, is that they create an unprecedentedly large amount of information, all of which needs to be easily stored, analyzed, and transmitted. Without these data storage and related capabilities, Big Data become cumbersome, unwieldy, and useless.
The federal government recognizes the inherent value of Big Data. In October 2014, the National Institutes of Health announced the distribution of nearly $32 million in grants to develop new tools that improve the usability of this information.
"Data creation in today's research is exponentially more rapid than anything we anticipated even a decade ago," NIH director Francis Collins, M.D., Ph.D., said in a statement. "Mammoth data sets are emerging at an accelerated pace in today's biomedical research and these funds will help us overcome obstacles to maximizing their utility. The potential of these data, when used effectively, is quite astounding."
Growth will continue in short term
According to an article in Health IT Analytics, the North American predictive healthcare analytics market is set to grow at a compound annual growth rate (CAGR) of 32.3 percent until 2019. When it comes to Big Data technology, the CAGR between 2014 and 2018 is 32.14 percent.
According to the NIH, various medical research projects in the U.S. are also driving growth trends in Big Data. For example, The Cancer Genome Atlas is examining regions of the human genome that may be tied to more than 30 types of malignant diseases, while the ENCODE project focuses on segments of the genome that actually perform functions.
Grants tackle challenges
Despite the ongoing growth in Big Data accumulation, members of the research community face several challenges in handling this information. Obstacles include problems with locating and analyzing pertinent data, lack of data standards, and low adoption rates for such standards.
To help tackle these obstacles, the NIH grants are aimed at four goals:
By the end of 2020, the NIH projects that Big Data projects across the U.S. will have received $656 million in government investments.