The Michael J. Fox Foundation’s new online clinical study Fox Insight (foxinsight.org) is seeking volunteers with and without Parkinson’s disease. Fox Insight aims to gather the world’s largest dataset on the day-to-day experience of living with Parkinson’s disease (PD).
Anyone with a computer and an Internet connection can participate in Fox Insight. It is open to Parkinson’s patients worldwide, as well as people who do not have PD. During their first visit, interested volunteers consent to participate and provide information about their personal experience related to Parkinson’s disease through a guided virtual study visit made up of simple questionnaires. Fox Insight then prompts participants to come back every 90 days for subsequent “virtual visits.”
A variety of built-in tools also helps manage and optimize care. An Appointment Keeper, Physician Report, printable summaries of questionnaires and access to other recruiting PD clinical trials all are offered within Fox Insight’s dashboard.
Fox Insight debuted in March as Apple Computer announced its first foray into medical research through ResearchKit, a platform for the development of iPhone apps that can streamline patients’ contribution of data to research toward cures. In conjunction with the launch of ResearchKit, biotech Sage Bionetworks released Parkinson mPower, a patient-centered, iPhone app-based study of symptom variation in Parkinson’s disease, available for down¬load via the iTunes App Store. Sage and MJFF are now collaborating on the further development of mPower, and later this year will jointly conduct a study of participants contributing data through both mPower and Fox Insight.
“Today the technology exists to study and measure every aspect of Parkinson’s disease — and not just in a few dozen or hundred people, as has traditionally been the case in Parkinson’s clinical trials, but in hundreds or thousands. And not just once or twice a year in a clinician’s office, but 24/7,” says Todd Sherer, PhD, chief executive officer of MJFF. “For the first time, we’ll have data to help answer fundamental questions — like when in the course of their disease people should start taking levodopa in order to get the best symptomatic benefit, or how to accurately predict who will respond to certain treatments, or why patients progress at different rates.”
Changing the paradigm of clinical data capture
Traditional clinical studies, the final, vital stage of research before a new treatment comes to market, are the most expensive part of drug development, costing millions or even billions of dollars. Clinical testing also is slowed by a chronic lack of volunteers in sufficient number. This can cause the drug development process to stall and some trials must be repeated or scaled back. Even worse, potential new therapies can be abandoned. These factors individually and collectively lengthen the time it takes for new treatments to come to market.
“Patients and families know that their participation in research is a requirement to speed progress toward cures,” says Debi Brooks, MJFF co-founder. “MJFF is working to build the on-ramps. Technology-enabled solutions, such as mobile apps and virtual studies, cannot replace traditional clinical trials. But they hold immense potential to complement field-wide efforts, in part by opening the door to many more research volunteers.”
While cost and recruitment challenges necessarily limit cohort sizes of traditional trials, home computers and smartphones can reduce the burden of participation for thousands of individuals — collecting data at relatively low cost. Computing solutions for the analysis of large datasets also are rapidly growing in sophistication.
This creates an entirely novel opportunity to amplify the patient voice in research by tying unmet medical needs directly to outcome measures for drug development. Individuals’ health can now be tracked in detail using self-reported data and mobile devices equipped with sensors that continue to improve in their accuracy. According to a recent report in The Economist, currently about 2 billion people around the world have access to smartphone technology, and 80 percent of adults will use an Internet-connected mobile device by 2020.
Core to the MJFF philosophy, all data collected through Fox Insight will be de-identified and made available to researchers worldwide for independent studies. Making this data available to the research community at large can rapidly accelerate progress by reducing research costs and promoting replicable results. As always, stringent measures are in place to protect participants’ privacy. Any data that directly identifies a study participant is removed before data is transferred to researchers for analysis. Participants’ contact information will never be sold, rented or leased.
mPower/Fox Insight 2015 Combined Study
Later in 2015, MJFF and Sage Bionetworks will jointly conduct a study of participants contributing data through both mPower and the Fox Insight platform. The combined study aims to amplify the voice of Parkinson’s patients and elevate their role as partners in research.
mPower participants with a diagnosis of Parkinson’s disease will be given the opportunity to consent to provide their data to the combined study. Additionally, MJFF will make Fox Insight users aware of the opportunity to download the mPower app and participate in the combined study.
Pending results of the combined study, MJFF will further develop and customize mPower to leverage the potential synergies of the mPower mobile app study platform and the Fox Insight platform.
A commitment to developing emerging technologies for patient benefit
The Michael J. Fox Foundation is committed to developing emerging technologies for the benefit of Parkinson’s patients. In August 2014, the Foundation announced an ongoing collaboration with Intel Corporation to develop big data analytics and wearable technologies to speed Parkinson’s drug development. Intel has developed an open-source platform for data collected through wearable computing. The platform supports an analytics application developed by Intel to process and detect changes in the data in real time. By detecting anomalies and changes in sensor and other data, the platform can provide researchers with a way to measure the progression of Parkinson’s disease objectively.
In the near future, the platform could store other types of data such as patient, genome and clinical trial data. In addition, the platform could enable other advanced techniques such as machine learning and graph analytics to deliver more accurate predictive models that researchers could use to detect change in disease symptoms. These advances could provide unprecedented insights into the nature of Parkinson’s disease, helping scientists measure the efficacy of new drugs and assisting physicians with prognostic decisions.