Megan Doerr is a Principal Scientist at Sage Bionetworks.

She will be speaking at the BioData West Congress in April 2017.

1. Please introduce yourself, your background and your current role. 

My name is Megan Doerr. I am a licensed genetic counselor.

My career path has been a bit non-linear. My original training is as a botanist. My first jobs were doing grassland restoration in East Africa and the American Mid-West. After being nearly struck by lightening one too many times, I became a classroom teacher. I taught science to middle and high schoolers in Boston, London, and Cleveland. I loved it – kids are naturally curious as well as being tons of fun – it was a joyful job. But I really missed doing my own science.

I joined the genetic counseling community in 2006. From 2009 to 2015, I led the clinical development and implementation of Cleveland Clinic’s family history and risk assessment tool, MyFamily. While at the Clinic, I was able to get my science on with the support of the Center for Genetic Research Ethics and Law (CGREAL), a Center for Excellence in Ethical, Legal and Social Implications Research funded by NHGRI, at Case Western Reserve University. My collaborations with CGREAL steered me deeper into the intersection of genetics, research, and ethics.

I became a principal scientist within the Governance team at Sage Bionetworks in 2015. Sage is a non-profit dedicated to advancing biomedical research through open and collaborative science. My current efforts focus on forging strong, reciprocal partnerships between participants and researchers in decentralised mHealth research, including for the All of Us Research Program (Precision Medicine Initiative). Together with my colleagues, I have recently published a formative evaluation of participants’ experience with Sage’s entirely remote, app-based informed consent process.

2. What is the mission of Sage Bionetworks and what are their activities?

Sage Bionetworks is a 501(3)(c) non-profit research organisation. Our mission is to engage diverse communities of researchers around biological and analytical problems too complex for a single institution. Additionally, through our mHealth initiatives, we aim to invigorate and empower citizens to track their own health and contribute deep phenotypic data to research topics important to them. In plain language, Sage was founded to drag the scientific method into the 21st century by encouraging team science, involving non-traditional solvers, and employing cloud-based platforms for data sharing and analysis.

You can imagine that sharing of oodles of data, much of it human, with our focus on open, collaborative scientific partnerships and public release, necessitates robust data governance. Sage feels strongly that we, as researchers, have an ethical and moral obligation to participants to ensure that their data donations have the greatest possible impact. We have worked to create a transparent, participant-centered data governance framework that facilitates researchers capitalising on our data repositories for discovery.

3. Please tell us about the Bridge and Synapse in more detail. What type of data do they collect and share? 

Briefly, Bridge facilitates generation of data by dispersed individuals participating in mHealth research projects. Bridge is set of web services and software developer kits (SDK) for data collection, de-identification, and aggregation for mHealth studies. It is designed to securely manage data captured through mobile technology platforms. Bridge was launched in 2015 as the backend service supporting all of the first 5 ResearchKit studies, and currently supports data collection for over a dozen mHealth studies.

Synapse is an open source software platform for analysis and sharing of data both from mHealth and for data generated through “traditional” research efforts. Data scientists use Synapse to carry out, track, and communicate their research in real time. Synapse has robust data governance features that Sage leverages for public data release, as for the Parkinson mPower and Mole Mapper studies.

4. Do you have any interesting examples of collaborations that originated from these platforms? 

Sage’s raison d’être is collaboration: collaboration between researchers and collaboration between researchers and participants.

An example of researcher collaboration is the Accelerating Medicine Partnership for Alzheimer’s Disease (AMP-AD) Knowledge Portal, a partnership between the NIH 10 biopharmaceutical companies, academic research groups, and several non-profit partners. Each partner came to the consortium with an existing biological resource and plans to generate some form of molecular data off of that resource. To amplify their efforts, AMP-AD partners agree to share the data they produce immediately with the consortium, with scheduled quarterly public data releases of all contributions. Deposited data includes gene expression, genotype, methylation, CHiP-Seq, DNA methylation, miRNA profiles, and clinical data. Contributing to and benefiting from a shared repository accelerates novel target identification and validation, a classic cross-pollination.

An example of researcher-participant collaboration is mPower, an app-based, entirely remote research study focused on tracking within-day fluctuations in certain Parkinson disease symptoms. In mPower, participants have access to their own data and themselves decide if and how broadly their data is shared. We have found our participants are enthusiastic citizen scientists, with hundreds sharing observations back with our research team. Further, about 7 in 10 have designated their data for the broad data sharing. Commensurate with their wishes, in March 2016 we publically released data generated by 9,500 participants through our Qualified Researcher Program, a light-weight, transparent data governance process designed to encourage non-traditional players to engage with these data. Researchers write an intended data use statement that is shared back with the community through the mPower Public Researcher Portal. One year later, more than 90 researchers from around the world have gained access the mPower data set.

5. What, in your experience, does incentivise people to share data?

Within the United States, it seems as if there is a groundswell of support for data sharing from research participants and patient advocacy organisations, as we have seen in our mHealth studies like Parkinson mPower. Their demands seem to be slowly reaching the ivory towers and we are beginning to see a slow shift in culture.

Funder mandates are further greasing the rails. For example, within AMP-AD, unbending funding mandates required data sharing from the start of the consortium. At first, there was some recalcitrance, but over time partners have begun to trust each other and the process, as well as to reap the benefits of the shared data resource. Now, in our third year, we find sharing comes quickly and easily across the consortium.

Second piece of incentivising data sharing is workflow. Making it easier to share than to not share, and making it easy to share early in the scientific discovery cycle, before the publication, is critical. If data is “born” digital and set up properly from the start on a shared platform, then it is not hard to share. Sage developed Synapse and Bridge to support data sharing from the inception of research studies, both of our own mHealth studies and for research efforts around the world.

The work of DNAdigest is made possible due to our sponsors.

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