Big Data And The Journey To Personalized Medicine
Personalized Medicine is a revolution that is unfolding at this very moment. The role of the physician will change dramatically, diagnostic and treatment quality will improve greatly, and wearables and devices will be part of daily life. Welcome to the Internet of Things for Patients.
These are just a few conclusions from the clinicians, bio-informaticians, geneticists, analysts and government and NGO-representatives that gathered at two recent conferences: the Biodata World Congress (Cambridge, UK), and the Big Data in Healthcare Symposium (Munsbach, Luxembourg). I had the pleasure to join both; below some of my conclusions.
Handling of medical data is not a big data issue
Any organization can handle and store Big Data; this is simply a matter of scaling. But how to make sense out of the data? Companies and organizations will have to become digital to remove the data silos, to make the most out of the information. This applies to physicians and researchers that are involved in improving the treatment of patients. Several national cohort and genome-projects already provide a big wave of information.
In the near future, patients will own that data, not the physician, but for the time being the latter must be able to make sense out of it, to be able to provide optimal council. Analytics and visualization will become more important, to find the signal in the noise.
Affect on pharma
The pharmaceutical industry is equally affected by the digitization challenge. As one of the representatives bluntly stated: “our industry is not used to handling data.” It was no surprise that Eroom’s law was referred to by many speakers: pharma needs to increase its output but the cost of the R&D workforce is also too high.
As a result, disruptive shifts occur: mobile phones may become medical devices, and some companies that own the consumer data may start to set the pace for pharma, not the other way around. The strategies by which pharma tries to get the most out of data are manifold, but all speakers stressed the importance of collaboration, both within the company, the industry, as well as with academic initiatives and providers.
Data privacy and security
The opportunity for genomics to produce better care is obvious, but what if insurance companies, government agencies, or even hackers gain access to the data? Clearly, the cancellation of the safe harbor agreement has created considerable uncertainty. However, as several speakers pointed out, the data security challenge is not unique to genomics (the banking, security and the healthcare industries have been handling private data for decades).
A sound security concept that combines stringent access-right management with industry-grade standards can alleviate many of the concerns. On top of that, criminal prosecution of data theft is a powerful deterrent; and already in place.
Taken together, these two events provided compelling insights into the status and future of personalized medicine. Many data, analytics, legal and moral challenges are not yet fully resolved, but the pieces are beginning to fall into place.
Ramin Sarajari’s comment:
What is the definition of big data?
Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.
Business Intelligence (BI) is a set of technologies and processes that help decision makers use data to understand and analyze performance. BI is the use of fact-based management to drive decisions and actions.
Business Intelligence helps find answers to questions you know. Big Data helps you find the questions you don’t know you want to ask. So with BI and Big data knowledge you can predict new events.
In next posts we will see how can big data improves medical diagnoses?