Big Data have the potential to change the world of medicine and the healthcare sector. It is a phrase that we actually hear very frequently among experts, but what does it mean specifically? It means, for example, the possibility of creating predictive analytical models based on DNA in order to prevent diseases which could arise in the future, it means having material available to predict the critical issues which will affect an organism and to be able to address the problem before it actually occurs; obviously these are just examples and there are many and various applications.
Big Data and health: large companies are aware
In this context, there are many companies investing in order to improve healthcare and transform medicine: just think of IBM who acquired Merge Healthcare in order to increase the health care skills of Watson, its “super computer” for cognitive computing, which will be able to “see” medical images, extracting and analyzing what, according to the company, represents at least 90% of all medical data today.
Google has also never stood still in this sector and has always focused on cloud computing capabilities: an example is its partnership with the Broad Institute of MIT and Harvard to launch the alpha version of the Genome Analysis Toolkit (GATK) on Google’s Cloud platform; the software, developed by the Broad Institute and was designed to help researchers to quickly analyze genomic sequencing data, has been made available to academic researchers at no additional cost beyond the standard price for using the Mountain View cloud; the use of GATK through the cloud is actually part of an overall service called “Google Genomics”, the company’s cloud computing platform devoted to biological research.
Google and IBM are just examples of how large companies look at the world of data (and at Big Data) in medicine: if companies of this size have decided to enter this market, one wonders what the real potential of Big Data for medicine and for the future of human health may be.
The true benefits of Big Data in medicine
Dr Eric Schadt, founder of the Icahn Institute for Genomics and Multiscale Biology, answers this question by stating that
“one of the major limitations that today’s medicine and the pharmaceutical industry have to face is the lack of understanding concerning biological information relating to diseases; Big Data come into play aggregating more and more information on how diseases are structured, whether pertaining to DNA, proteins and metabolites, tissues, organs and ecosystems.“
If we begin to utilize this analysis technique, according to Schadt, the models will evolve and will have the ability to become predictive towards certain types of illnesses.
Wanting to be more specific, as did the Hiss Journal (Health Information Science & Systems), it is possible to split the impacts according to areas, identifying actual scopes of innovation:
Research and Development
- with Big Data, it will be possible to create predictive models in order to streamline processes concerning the creation of medicines and medical instruments;
- statistical tools and algorithms can optimize the analysis of clinical trials, reducing unsuccessful tests and consequently increasing the speed with which new treatments enter the market;
- the analysis of Big Data may also have effects on the data of patients who experiment new drugs, identifying possible adverse effects not taken into account before the treatments are placed on the market.
- it will be possible to analyze the spread of disease patterns and to track outbreaks to improve public health surveillance and increase response speed to emergencies;
- increase the speed of development of vaccines and “calibrate” them more accurately through, for example, a more precise choice of the annual influenza strains thanks to the use of predictive models;
- transform large amounts of data into useful information which can be used to identify people’s needs and anticipate and prevent crises, even in single individuals.
- Big Data could make genomic analysis more efficient and cheaper, placing it within the normal decision-making process for medical care, enriching the data available in the patients’ medical records.
- real-time collection and analysis of large volumes of rapidly evolving data both in hospital and at home through different types of devices (for example, wearable devices), will have a strong impact on the prediction of adverse health events (heart attacks, strokes, etc.);
- applying advanced analytics to profiles of single patients in order to identify people who could benefit from preventive treatments or from a change of lifestyle: a prime example is given by patients who are at risk of developing a specific disease (e.g. diabetes).
In conclusion, the implications of Big Data in medicine are so strong that they could have a very important role for the development of medical science; using, once again, the words of Dr Schadt, however,
“… it will not be a reasonable increase in awareness which will make Big Data operational in this field overnight. The process must be seen as an evolving continuum, a continuum which will bring progress in an extraordinary way.“