With the cost of mapping an individual human genome poised to break several financial barriers, bringing personalized medicine closer to reality, the healthcare and life sciences industries are now grappling with managing the explosive growth of data and information. Big Data is a buzzword, or a catch-phrase, used to describe a massive volume of both structured and unstructured information that is so large that it’s difficult to process using traditional databases and software techniques. Life Sciences and Biomedicine have been highly affected by the generation of large data sets, specifically by overloads of genomics information. Applying downstream analytics in a volatile data environment, overseeing data storage and movement, and transforming the data to improve patient outcomes and quality of life are just some of the challenges faced today in this field. In this regard, more sophisticated, innovative and robust information technology is being developed to aggregate, manage, analyze and share Big Data. In order to deal with this overload of information in life sciences, the Obama Administration launched a U$200 million Project in 2012 named “Big Data Research and Development Initiative”, which aims to transform the use of Big Data for scientific discovery and biomedical research, among other areas. The White House claimed in a statement that in the same way that past Federal investments in Information Technology Research and Development have led to dramatic advances in supercomputing and the creation of the web, this initiative will transform our ability to use Big Data for scientific discovery, environmental and biomedical research, education, and national security. It is indeed critical to collaborate and use tools to facilitate the technology ecosystem to develop innovative solutions to seemingly intractable problems emerging in healthcare today. This is mainly because Big Data presents a challenge that is so big and so complex that no single individual, company or institution – no matter how accomplished or illustrious – can solve it alone. Importantly, biomedical infrastructure for Big Data analytics lags behind the curve and new solutions both in hardware and software will be necessary to overcome the obstacles. Big Data in Biomedicine can pave the way in healthcare to a better understanding of people’s health and disease, especially now that mobile devices such as tablets, phones, watches and others have been implemented to collect an individual’s health information. I believe that the methods used by Facebook, Twitter, Google and other big corporations (such as commodity hardware, open source software, and ubiquitous instrumentation) to deal with big chucks of information will prove just as revolutionary for healthcare as they have for communications and retail. This new revolution could mean changes in clinical care, however challenges such as privacy of the information are a big barrier. Solutions to deal with privacy and security have been developed recently but this field is in its infancy, opening up opportunities for new ideas and technological breakthroughs. It is an exciting time now that both Information Technology and Biomedicine are converging in the Big Data era. A lot of interesting developments will happen in the next five years or so and we will need several Big Data solutions to deal with health information.
