Data is, of course, driving the future of healthcare. Stakeholders across the industry have been widely preparing for the Big Data transformation and how to put the data to best use. At the recent Financial Times Global Pharmaceutical and Biotechnology Conference titled “Embracing Disruption for a New Era in Health,” several experts examined how to get to the next level of data use, and the consensus was that the future is sooner than we think.
Pamela Cyrus, vice president of global governance at Bayer, said we are getting to the point where the ability to use data is now the differentiator rather than the data itself. There is certainly no shortage of data, which is increasingly consistent and “usable,” she said; however, the main obstacles remain fragmented datasets and concerns over data ownership.
Peter Donnelly, CEO at Genomics plc, said that fragmentation of data cannot be pinned on patient records alone. Although this is part of the problem, data sharing across all data is the biggest problem because the starting point of most stakeholders is “How do I lock my data?” rather than “How do I share it?”
Regarding better data sharing, Donnelly said that disruptive thinking was required, potentially through the generation of new partnerships with technology firms. The situation may be simpler in the UK, where the National Health Service is very much viewed as a public resource, which may allow simpler discussion with patients about the value of data, but the same issues remain about privacy and consent.
“Regarding better data sharing, Donnelly said that disruptive thinking was required, potentially through the generation of new partnerships with technology firms.”
The UK government is also considering models to evaluate how this value feeds back into the system. Key points remain on the quality of the data, but Donnelly also said that there is too much obsession with “clean” data; we may be removing the signal with the noise and instead we must let the data speak for itself, he said.
What about wearables?
Turning to data from wearables, the panel agreed that feeds from these and health apps can be an important data source even if not medically validated. There will invariably be a signal in this data; however, if beginning from the position of “this won’t be clinical-grade data” then nothing will be learned from it. Knowing about patient behaviors and lifestyles outside of their clinical condition provides opportunities, and the environment is ripe for disruption; however these are not yet coming together.
The consensus was that medical devices need clinical-grade data as these need to be formally regulated, but nothing else does.
Finally, an end-to-end capacity to analyze data is needed, and at that point, the question becomes the information derived from the data as opposed to who owns the data. In healthcare this data is not currently accessible enough, the speakers agreed, but progress in machine learning and artificial intelligence (AI) is progressing. An important benefit that could derive from this could be in imaging, where straightforward wins would be possible given the applicability of AI to image abnormality detection; however, it could also change how healthcare systems think about genetic risk, given that those at the highest genetic risk of a disease are currently usually completely invisible to the system.
This article was excerpted from the author’s full report from the Financial Times Global Pharmaceutical and Biotechnology Conference: Embracing Disruption for a New Era in Health, which convened in London in November. Other session topics included in the full write-up include:
- the future of diagnostics;
- how China has become an increasingly significant disruptive force in healthcare;
- the changing shape of biopharma deals and collaborations;
- patient-centered care; and
- a look at the success of the UK’s life sciences economy.
The report appears in Cortellis, from Clarivate Analytics, and is available here.
