In today’s post, Elettra Ronchi of the OECD Science, Technology and Innovation Directorate argues that our current model of innovation has so far failed to deliver the effective treatments that we urgently need for the 44 million people living with dementia worldwide, and asks if recent advances in information technology can come to the rescue.
There’s a quiet revolution afoot: health data are increasingly collected, stored and used in digital form. Doctors, nurses, researchers, and patients are all producing on a daily basis huge amounts of data, from an array of sources such as electronic health records, genomic sequencing, high-resolution medical imaging, ubiquitous sensing devices, and smart phone applications that monitor patient health. In fact the OECD predicts more medical information and health and wellness data will be generated in the next few years than ever before.
The remarkable expansion of digital health data is largely driven by technological developments, not least the expansion of broadband access, smart mobile devices and smart ICT applications. Improvements in data analytics have also played a significant role, as has the provision of super-computing resources through cloud computing.
This revolution could prove particularly helpful for neurodegenerative diseases like dementia. Because of dementia’s clinical and biological complexity, the studies needed to underpin drug discovery and develop new therapeutic strategies aimed at slowing disease progression will require massive and diverse data collection, storage and processing. And large quantities of broad and deep data are being generated across laboratories worldwide –the information is behavioural, genetic, environmental, epigenetic, clinical, administrative, and more. Harnessing this data, advocates argue, would present advantages across the board: for research, patient care, health system management, and public health.
So how can we foster this environment where data aids dementia innovation? Today, researchers’ willingness to share data is often constrained by uncertainty. Several issues are at play.
First, ethical concerns need to be accounted for. Currently, informed consent permissions, which cover the consent for the use of the participant’s data, tend to be limited to the research questions related to the primary study focus. This means they exclude potentially unrelated investigations that could follow from open access to these data in the wider research community. New tiered step-by-step or dynamic consent models are needed to meet ethical and legal requirements and at the same time accommodate the changes in data use and research practices.
Second, there are broader challenges to data sharing, related to the lack of an open data culture. Open science has an enormous potential to avoid wasteful duplication of effort, to enable the verification or scientific results and the re-analysis of data for different purposes, and to promote competition of ideas and research. In 2013, the G8 Science Ministers statement called for publicly funded scientific research data to be open.
Yet there are still considerable disincentives that researchers and scientists face with respect to the disclosure of data, particularly at the pre-publication stage. Credit sharing in the academic economy presents dilemmas for researchers. Publications by whole consortia or with numerous authors are a challenge for academics concerned about how these publications will be credited and recognised for career promotion by their institutions. This raises the question of the actions needed to promote data access and openness to boost research and innovation without discouraging data collection from individual researchers.
Third, there is a need for investment in order to harness the potential of data for dementia. The costs of collecting, storing, linking, organising, and analysing data require considerable investment and collaboration, and appropriate funding needs to be set aside. Sustaining the big data infrastructures will also require financing: for many big data projects, networks or federated research platforms, the most significant challenge once the initial funding runs out is the development of a sustainable business model, that as a bare minimum, would sustain the curation and maintenance of data in an accessible form.
Big data also requires large numbers of people who are very highly trained and in huge demand from other sectors. Data specialist skills could become the most critical enabler for big data dementia research. Incentives are needed to promote education and training of data analysts and bioinformatics experts to use big data effectively for health research.
Of course, the explosion of promising new technological opportunities and data generation will not automatically translate into new products and care solutions for dementia and other neurodegenerative diseases. In order to deliver this promise, these new developments will have to be accompanied by organisational, infrastructural and governance changes throughout the health innovation system. The current R&D process is fragmented, costly, unpredictable and inefficient. Funding for dementia and other neurodegenerative diseases accounts for less than 1% of research and development budgets in the G7. These, and other issues, will also need to be addressed.
Researchers in industry, hospitals and universities continue to make significant contributions to scientific understanding. But without better data sharing, interpretative capacity, and co-ordination of knowledge, we can make only limited progress in our understanding of the molecular basis of neurodegenerative diseases or whether treatments or interventions work. Radical improvements in information technologies and the increasing gathering and sharing of electronic health data not only make it timely to assess and improve global capacity to undertake multidisciplinary research – they make it imperative.
Big Data for Advancing Dementia Research: An Evaluation of Data Sharing Practices in Research on Age-related Neurodegenerative Diseases OECD Digital Economy Papers, No. 246
Dementia Research and Care: Can Big Data Help? Edited by G. Anderson and J. Oderkirk
Unleashing the Power of Big Data for Alzheimer’s Disease and Dementia Research: Main Points of the OECD Expert Consultation on Unlocking Global Collaboration to Accelerate Innovation for Alzheimer’s Disease and Dementia, OECD Digital Economy Papers, No. 233