As we ring in the new year with health and well-being top of mind, it’s highly beneficial to proactively manage our health efforts with a complete understanding of what “good health” truly is. Some may argue that good health is the mere absence of disease or infirmity, however according to the World Health Organization, good health is actually the state of complete physical, social and mental well-being.
For years, my wife experienced chronic migraine headaches. In order to proactively manage this condition she kept a diary, tracking the details of her experiences, from how she feels each day, to her activities, and what she eats. As a result, she’s identified patterns of health and migraine triggers beyond what her doctor has been able to identify. Based on her findings, she adopted a Gluten-Free and Dairy-Free diet and participates in daily exercise to alleviate the extensities of her headaches and prevent any further health issues.
My wife is one of many people who live with chronic health conditions. According to the National Health Council, 40% of the US population suffers from some type of chronic condition, including but not limited to fibromyalgia, depression, digestive problems, arthritis, and lack of focus. So what can we do about it? Much of the low-hanging-fruit, in terms of understanding the causes of various diseases has been identified but the diagnosis for the remaining conditions involve putting patients into “clinical buckets.” These diseases that remain untreated are more complex and remain medical mysteries. Discovering the underlying basis of these unsolved conditions requires the analysis of a deep data collected over time, including genomic, EHR, and private or daily personal data. Acquiring this data requires the participation and engagement of hundreds of thousands, if not millions, of people. Institutions are therefore dependent on the trust of individuals to enable broad data sharing, however once trust is earned and data flows to the institution, what’s the incentive for the individual to keep contributing? Why should we contribute our personal and health data in the first place and continue to contribute this data over time? What will we receive in return for our efforts?
Studies show that 10% of our health is determined by what happens within the walls of a healthcare provider, 30% by our genetics, and 60% by environmental and behavioral factors. This last 60% is only accessible with the engagement of the individual. Discovering the basis for complex diseases can happen using artificial intelligence to analyze very large sets of genomic, medical, environmental, and personal data. Once enough people with the same illness or condition, and in many cases similar genetics, health habits, demographics, etc., share their data, artificial intelligence programs will decipher the underlying causes of the condition. AI can determine why a condition may specifically affect some people and not others despite having the same genetic markers or environmental exposures. Family, friends, and others in our community will reap the benefits of these discoveries for generations to come.
My would have loved to have a central place to record her health information instead of writing in notebooks. Moving our health information from conversations, jotted records like my wife’s, EHR’s, or even data that we haven’t shared or documented yet, to a structured, central location, will assist us on our own health and wellness journeys. If stored correctly, the data can fuel artificial intelligence algorithms that will help us find the links between our daily routine and the status of our chronic disease. Was the chocolate my wife ate the day before a trigger for her headaches, or did her hard-gym workouts in hot dry weather bring on the migraine? On a simpler note, routine analysis could help us manage our weight, achieve our fitness goals, and steer away from behaviors that lead to lifestyle diseases such as high cholesterol, hypertension, and diabetes.
At some point in our lives many of us, or our family members, may suffer from debilitation chronic or acute diseases, such as early onset childhood ailments, cancer, and Crohne’s disease. Genomic data is changing the way we treat children with early onset diseases and diagnose the molecular basis for most cancers. Microbiome data is sequenced in our quest to understand gut ailments, such as Crohne’s IBD, and SIBO. The new problem we are facing today is that in many cases the penetrance of the genomic marker is low. In other words, for some ailments all persons with the exact same pathogenic mutation or modification of their genome do not all come down with the disease. The genomic mutation does not guarantee a person will suffer from the ailment or when in life it might occur. The genomic marker is not 100% penetrant. The reasons for this are many fold and not always understood. The causes of these conditions are often a complex interaction between different aspects of our lives including our genome, microbiome, environment, and our daily habits. Do we drink, smoke, exercise daily or work stressful work hours? The answers are within our grasp. Technology barriers are not the issue. The challenge is collecting deep data over time at scale.
Individuals would then be rewarded through the use of their personal data to help on personal quality of life improvement journeys whether the journeys be about resolving personal conditions or achieving personal goals. The data would first enable precision medicine for all participants while improving our day to day quality of life, our health, and provide the satisfaction of helping others with their own personal health journeys.
Luna’s suite of tools and services connects communities with researchers to accelerate health discoveries. With participation from more than 180 countries and communities advancing causes including disease-specific, public health, environmental, and emerging interests, Luna empowers these collectives to gather a wide range of data — health records, lived experience, disease history, genomics, and more – for research.
Luna gives academia and industry everything they need from engagement with study participants to data analysis across multiple modalities using a common data model. The platform is compliant with clinical regulatory requirements and international consumer data privacy laws.
By providing privacy-protected individuals a way to continually engage, Luna transforms the traditional patient-disconnected database into a dynamic, longitudinal discovery environment where researchers, industry, and community leaders can leverage a range of tools to surface insights and trends, study disease natural history and biomarkers, and enroll in clinical studies and trials.
Executive Chairman of the Board + CO-FOUNDER
Bob was Illumina’s Chief Engineering Officer and, during his 15-year tenure, helped grow the Company from a 30-person startup to a global genomics leader of 3,000 employees at $1.5 billion in revenue.