Technology enabling the democratization of research
By: John Doyle, DrPH, MPH | August 17, 2016
This is the ninth in a series on trends impacting the biopharma industry.
Mobile, cloud, sensors, social media technologies and analytics offer new opportunities for innovation in patient care and connectivity. The convergence between patient-centric approaches and digital technology is fundamentally changing the way patients collect and share their healthcare data, creating vast stores of real-world data to inform the development and delivery of new treatments. Makers of monitoring devices are taking this consumer-driven health care to the next level, with many research initiatives targeting chronic conditions that are costly to treat. Used in partnership with patient advocacy groups, these technologies promise to democratize research by enabling extensive data collection and sharing.
Historically, patient data has been used for research in pooled databases, but Steven Keating, a graduate student at the MIT Media Lab and brain cancer survivor argues these new tools that offer ‘huge crowdsourcing opportunity.’ And we’ve already seen this model put into action. Wearables are increasingly being used in clinical trials, with close to 300 trials currently underway using such technology. The National Institutes of Health (NIH) is considering using smartphones and wearables for data collection as part of the White House’s Precision Medicine Initiative. In addition to collecting data during a trial, such devices have potential to reduce screen failure rates by qualifying participants in advance.
The launch of Apple’s ResearchKit now allows researchers to recruit subjects and collect their data from iPhones or iPhone-linked fitness monitors, such as Fitbit or Apple Watch. In October 2015, Johns Hopkins announced that its epilepsy study, EpiWatch, was the first ResearchKit App to use Apple Watch to collect patient data. Johns Hopkins’ EpiWatch modules enable participants to complete informed consent; track their seizures in real time; and answer research surveys. Users can review their data and compare their symptoms to others in their demographic with similar seizures.
In January 2016, The Michael J. Fox Foundation said it was working with Cynapsus Therapeutics and Intel Corporation on a pilot incorporating wearable devices and ‘big data’ into a phase 3 clinical trial of a potential Parkinson’s disease drug. The trial involves Cynapsus’ thin-film, under-the-tongue strip of apomorphine.
Telcare has launched an FDA-cleared diabetes monitor, said to be ‘the first cellular-enabled solution that connects everyone who can help you manage your condition: healthcare professionals, clinical services, educational resources, and your network of family and friends.’
Google is developing various apps and projects involving health data, using Google Fit to track fitness data and integrate information from third-party health apps. Google is also investing in health research through Google Genomics, a cloud storage service for DNA data, and has backed 23andMe, a DNA analysis service.
Reuters reported in June 2015 that Amazon.com was in a race against Google to store data on human DNA, a market that may be worth $1 billion a year by 2018. Academic institutions and healthcare companies are reportedly picking sides between the two companies’ cloud computing offerings, Google Genomics and Amazon Web Services. Microsoft Corp and IBM are also competing for market share.
What does this mean for biopharma?
Biopharma should continue down this path of exploring and piloting technology-based solutions in their clinical trials but not stop there. The same technology used to improve efficiency of the trial process and enhance interactions with clinical trial patients can be deployed to enhance the customer experience in the market.
Companion devices – non-invasive health devices that accompany drugs – can provide information on the effect and delivery of drugs. Using mobile health (mHealth) capabilities, these devices remotely monitor health data, providing an opportunity for more frequent personalized. The challenge with such devices is making them financially viable and obtaining reimbursement. Examples include Mobile Prescription Therapy (MPT), such as Welldoc’s BlueStar the first mobile app approved by the FDA for management of type 2 diabetes; disease centered devices used in the clinic; and drug-device combinations such as inhalers, transdermal patches, and nebulizers.
Notwithstanding the tremendous promise of these technological advancements, limitations exist. Generalizability is a concern. For instance, some evidence suggests that uptake of wearables is greater among men than among women. Also, wearable users may behave differently when being monitored – a phenomenon known as the Hawthorne Effect. Concerns around data privacy remain. If we can overcome these limitations and truly democratize research, patient research will transform to population research in the near future.