Big Data. Hope for patients.
It was supposed to be a solution accelerating medical scientific research, individualisation of treatment, or development of new drugs. In short, a chance for a better future. The visions of using big data in order to explain the mechanisms of a human body appeared to be hypothetical when confronted with market reality, i.e. limitation in access to data and low social approval of data use for scientific purposes. However, new hopes are being raised by innovative projects in medicine, pharmacy and biotechnology, discussed by experts during the BIONNALE 2017 conference in Berlin.
A few years ago, the expression "Big Data" had bad connotations, as it was associated with the knowledge collected by global corporations such as Facebook, Amazon or Microsoft, with obscure information flow, or even with illegal information trading. "Big Data will take over our lives", newspaper headlines warned. When Google first attempted to use data collections to analyse the development of epidemiological situation, more precisely to forecast flu epidemics on the basis of search queries (Google Flu), it appeared conducting information analysis on a global scale is much more complicated than expected. After several grave prediction errors, Google abandoned the project, leaving a sense of disappointment with the new science. It was 2008, the time before the great digital revolution dominated by smartphonisation of society, digitalisation of medical information, and democratisation of access to knowledge.
Today, Big Data is once more arousing discussion, especially in healthcare, pharmacy and biotechnology. Recently, a dynamic development of new tools, which enable collection of information directly from patients, such as health applications or health monitoring devices, has been observed. Artificial intelligence has been introduced to scientific institutions across the world. Electronic patient accounts, which arrange our knowledge about man and provide material for scientific analyses, are becoming increasingly popular. Clinical studies have been using large data bases for a long time, even when the processing and analysis involved only paper records. Prof. Michael Krawczak, PhD (Christian-Albrechts University) believes that as for today, the development of medical data analysis is blocked by data fragmentation, incompleteness, lack of interoperability standards for information exchange, as well as data safety issues and legally unregulated rules of access. "The greatest challenge is to convince clinicians, doctors and patients to share information for the sake of science. Society cannot keep up with the technological development, and as a result, science is paralysed by the social factor. Without the symbiosis between technology and the human factor, it will be difficult to move forward", adds Professor Michael Krawczak.
Data digitalisation is a brand-new opening in the history of data collection, access and processing. However, the methods employed by science are still deeply entrenched in the reality of working with paper documents. The form of recording has changed, but the working methods have not. Clearly, revolutions do not take place overnight, but require time, adaptation and acceptance. The course and effects of the digital transformation depend not only on the leaders of innovation, but also on politicians who need to understand the potential of data. It appears that what is missing most in the approach to Big Data is empathy. Empathy for patients, for whom acceleration of research on new drugs and treatment methods is far more important than short-sighted debates about information safety. If someone raises this argument today, does not fully comprehend why science needs a new source of information, and how clinging to old methods is holding back scientists across the world.
In the backstage of ideological discussion, the concepts of Big Data are slowly being introduced. One of them is "Big Data for Better Outcomes Programme", conducted by IMI (Innovative Medicines Initiative), involving a few dozen entities from the EU. Using the information available on the market, experts want to develop new methods of medical decision making, identification of the best clinical practices, or increasing patient engagement in the therapy. The programme focuses on supporting evolution of health protection in Europe into sustainable, quality and outcome-oriented systems, according to initial objectives.
Another example, which perfectly illustrates the scope of Big Data potential, is Sea Hero Quest, a simple mobile game. The behaviours of players help scientists to better understand the mechanisms of dementia. So far, the game has been played by 2.5 million people. A few dozen years would be needed to gather such a numerous group of volunteers for traditional clinical studies. Interestingly, the already collected data present the equivalent of 9,500 years of scientific research. It is easy to imagine the results, which could be obtained by collecting more complex data from various sources.
Dr Mathias Bädeker from Boston Consulting Group points out a very scarce use of Big Data in pharmaceutical industry or in research and development projects. "The effects of digitalisation on the biopharmaceutical industry are much more limited than in other areas, such as logistics, media or motor industry. It is partially due to the fact that health care is a very closely regulated sector", emphasises Dr Bädeker and adds that using digital solutions in biopharmacy will be one of the key factors supporting scientific research. To this end, a change is required in the organisational culture, and restructuring of current data processing methods.
One might say that Small Data is the new Big Data. Thinking about big, global data collections, we need to start working locally, on the basis of information collected in small areas, in individual bases. Before we access external sources, first we should determine what information we have in our institution, and how it can be consolidated. Most importantly, we need to share information, as this is the only way to support the development of science. Internal data collections can be of much value if we know how to integrate, process and analyse them.
We all face an equally important task. If we, as a society, patients, and people, want to benefit from personalised medicine, new treatment methods, prophylaxis, more effective and safer pharmaceuticals, we must understand that it will not be possible without our own input, and permission for anonymous use of data, e.g. from our health accounts. We need to change our thinking about information from an individual to a collective approach. We are living at times of intensive development of sharing economy. Open data exchange, open research data access or data donation should be the focus of discussion, both in science and in politics, on the topic of digitalisation of medicine and pharmacy sectors, as well as about using Big Data in scientific and political research.
Digitalisation is everywhere. It is awaiting medicine and pharmacy. Walmart, an American supermarket chain, is creating its own clinics; Amazon, a world leader in Internet shopping is investing in the pharmaceutical market, and Swiss Post is testing drones for transportation of laboratory samples between hospitals. "The future of health care is in prediction, prevention, decentralisation, individualisation, continuous care, consumer advantage, and shifting to an outcome and quality-based medicine model", says Dr Zayna Khayat (REshape Health Innovation Centre, Radboud University Medical Centre). Health care will be based on access to the information collected from different sources, describing patient behaviours and health conditions.
Medical science and Big Data are a couple with a bright future ahead. If we do not want to waste excellent opportunities, we need to be open to a change in our current philosophy of information sharing. Dr Kai Bindseil (Health Capital Berlin-Brandenburg, Berlin Partner for Business and Technology) aptly said that those who conduct their activity in isolation are bound to fail.
"Small Data is the new Big Data"
"Digitalisation is a brand-new opening in the history of data collection, access and processing. However, the methods employed by science are still deeply entrenched in the reality of working with paper documents".