A: The old way of engaging with clinical trial participants needs to evolve into a model that is more collaborative and participatory. Research “subjects” need to morph into research partners that are genuinely interested in the study being conducted, both in the here-and-now and in the future state, through longitudinal engagement.

A: I envision a future where any community can organize around a research question; drive the aggregation of the necessary data; and support the broadest vision of who can be a researcher. This is embodied in the open science movement; however, more progress is necessary in the near term.

I look forward the transformation of future data collection and I can envision a day that’s connected through wearables, sensors and internet of things where we can simultaneously live life while donating our “digital bodies” to science. The opportunity and imperative today, however, is to operationalize people-first principles in data control, transparency, privacy and value sharing so that we properly engage individuals as partners in research. The scientific community’s insatiable hunger for larger and richer data sets will be met by the scalable and contextualized life data that’s representative of our diverse communities.

A: Please see below for additional questions and answers for your consideration.

A: While patients have greater access to their medical data now more than ever before, the medical data provided through patient portals falls short of what researchers require to advance medical knowledge. I believe patient portals will evolve from supporting data access to forming a conduit for enhanced, real-time engagement, convenience, and consolidation of all of your health data in a central location. Moreover, there is increasing sensitivity that patient data is a valuable asset that’s being bought and sold regularly, often without individuals’ knowledge or consent.

There is demand for this data, as researchers are increasingly calling for real-world, longitudinal data to make transformational discoveries. The LunaDNA platform was founded to operate at the intersection of individual data access and empowerment and research acceleration to cure disease. We are bullish that these forces of change and opportunity will push the entire health data landscape to modernized systems and empower people to share their health data for the greater good of health research.

A: Underrepresented communities in research weakens the scientific generalizability and clinical applicability of discoveries and interventions. Explanations of failure to achieve diversity in health research are well documented and range from past injustices to simply failing to offer greater value than risk or effort. Engagement and trust are not achieved by hosting a single meeting and giving away free testing kits, and people-centricity and individual control are much more than de-identification.

Achieving balanced representation and diversity can provide a richer perspective on the issues, which in turn suggest solutions or approaches that would otherwise lie unexplored. Increased diversity also promotes an ability to observe relationships within the data that remains hidden in more homogeneous data sets. Lastly, diversity also leads to an increased level of trust due to a broader representation of peoples’ interests. Without trust, we hurt our ability to improve health for all.

A: LunaDNA was formed to reshape research from a transactional snapshots of study subjects to relational, continuous engagements. This is best achieved by individuals recognizing that they are the best curators of their personal health information. Trust is vital in any relationship and we see data sharing as a dynamic relationship that is constantly re-assessed based on kept promises. As an ethical business, our model puts people first, operationalizing core beliefs that transparency creates trust, increased control enhances trust, and reciprocity maintains trust. Opt-out, consent, and unfavorable terms tucked deep in lengthy legal documents are not trust-earning instruments, but have been successful tactics to acquire data. In an increasingly connected, digital and data-mindful world, we have the opportunity to both honor individual’s needs in a data-sharing relationship and create a remarkable platform for research.

A: Since no system is 100 percent penetration-proof, it’s important that people are fully aware of the risks in data generation and confident in their data sharing decisions. To eliminate risk, LunaDNA’s platform de-identifies, encrypts and segments the data to remove context for each data element. Our architecture is designed to split out data, such as authentication credentials, transactional records, genomic data and phenotypic content.The intent is to ensure that if any data is compromised it cannot easily be linked back to other records. This segmentation of information ensures our threat avoidance measures are exponentially more effective, as multiple, independent attacks would need to occur to gather enough data what would compromise the privacy of an individual.