Chairs and Moderators: Nahum Gershon, MITRE, and Justin Sanchez, DARPA
Dave deBronkart, e-Patient Dave, International keynote speaker, author and health policy adviser. See: email@example.com
Wendy Nilsen, Program Director, Smart and Connected Health Division of Information and Intelligent Systems Directorate for Computer & Information Science & Engineering National Science Foundation
Larry Smarr, the founding Director of the California Institute for Telecommunications and Information Technology (Calit2), a UC San Diego/UC Irvine partnership.
Advances in technology and analytics have provided us with the possibility of measuring and analyzing medically related data and information about a person’s daily life (inputs, states, and performance). The combination of embedded sensors, wearable computing, and personal input has recently enabled people to monitor their personal physiologic condition in ways that have not been possible before. Persistent physiological monitoring has the potential to transform medical practice and the way that consumers interact with their biology.
Could these new data and information streams and analytics supplement traditional primary care medicine and enhance the collaboration among patients and medical practitioners? Or, are they going to radically change the paradigm though which consumers visit, interact, and receive care from their medical practitioner?
Furthermore, there are many technical and engineering challenges. Among them: Could too much data become a disadvantage?
Could too many sensors interfere with the body’s normal functioning?
Does close monitoring always find something wrong? Is abnormality normal? Could a person’s privacy be of concern?
Could close and constant monitoring drive people to improve their life style or vice versa?
The symposium will explore what is available today, what is expected in the near and far future, what are the challenges, and how they could be resolved. It will also explore the expected future of medicine in light of a more significant participation of the patient in his/her medical information collection and analysis and the expected future collaboration among patients and healthcare providers.
13:40-14:05: Dave deBronkart, e-Patient Dave, International keynote speaker, author and health policy adviser.
Presentation title: I Barely Survived Cancer and Nobody Knows Why
14:05-14:30: Wendy Nilsen, Ph.D., Program Director, Smart and Connected Health Division of Information and Intelligent Systems Directorate for Computer & Information Science & Engineering National Science Foundation
Presentation title: Turning the Quantified Self Into a Healthier Population
14:30-14:55: Larry Smarr, Ph.D., the founding Director of the California Institute for Telecommunications and Information Technology (Calit2), a UC San Diego/UC Irvine partnership.
Presentation title: Linking Phenotype Changes to Internal/External Longitudinal Time Series in a Single Human
I Barely Survived Cancer and Nobody Knows Why
“e-Patient Dave” deBronkart
Blogger, keynote speaker, policy advisor e-Patient Dave LLC
Chair Emeritus, Society for Participatory Medicine
Anyone who’s worked in technology knows how rapidly things can change when important information becomes available in new places, and the era in which pure raw data helps produce better biology is arriving. But we ave a long way to go before it reaches everywhere it’s needed.
After a career in high tech marketing, in 2007 I was diagnosed as almost dead with metastatic kidney cancer. I partnered with world class physicians and also with an expert online patient community, received an immune system treatment that usually doesn’t work, and in six months had beaten the disease – one of the early miracle cures produced by immunotherapy. But nobody knows why I survived and most don’t. More perplexing, I was in a clinical trial for a new use of the drug, and I was in the arm of the study they thought would NOT respond. This might seem astonishing but the truth is that until the 1990s medicine didn’t even know what cancer is (broken DNA), and not until very recently did we begin to understand the genome.
But breakthroughs are happening in patient self-monitoring: the OpenAPS movement is letting people with diabetes achieve results not possible before through self-monitoring, other disease communities are clamoring to do the same, and it will surely come to cancer. And that begs the question:
Could the future be better with more patients actively engaged – and doctors opening up to these possibilities – or do we really need technology, too, to patients are better able to monitor themselves?
Turning the Quantified Self Into a Healthier Population
Program Director, Smart and Connected Health Division of Information and Intelligent Systems Directorate for Computer & Information Science & Engineering National Science Foundation
The rise of self-monitoring devices (e.g., physiological monitors) has yielded a considerable amount of data, but very little evidence that self-tracking has improved health. The first wave of self-monitoring captured data from a highly motivated population, the quantified self movement, with devices that were often inaccurate or challenging to use. The next generation of the self-monitoring should herald the development and adoption of self-monitoring devices in which the form factor has been improved, user interface simplified and the quality of data enhanced. Evidence of these changes have been clear in the scientific community and suggest that the quantified movement may become a much broader effort toward a healthier population movement. This talk will explore the opportunities in the next generation of self-monitoring devices that are unobtrusive and easy to use so that those most in need can be easily served and the data used to improve their health. It will also examine the challenges to the interdisciplinary science required to successful develop devices that can fulfill these goals.
Linking Phenotype Changes to Internal/External Longitudinal Time Series in a Single Human
Larry Smarr, Ph.D.
Founding Director of the California Institute for Telecommunications and Information Technology (Calit2), a UC San Diego/UC Irvine partnership.
Taking the point of view that the human body is a dynamical coupled system, I have been involved in an experiment for most of the last decade to gather time series data on key body variables. By taking blood and stool samples on a regular basis (bimonthly to quarterly), I have developed a detailed longitudinal time series of ~200 biomakers as well as the microbiome ecology. To define phenotype changes, I have daily weight and symptom data, as well as wireless sensors. Since I have colonic Crohn’s autoimmune disease, one seems episodic variation in these variables with excursions of 10x to 100x above healthy values, demonstrating that single values of these variables randomly taken in time (i.e. traditional medical care) is nearly meaningless. I also have discovered a major shift in the microbiome ecology that is strongly coupled to changes in prescription medicines and external variables such as weight and autoimmune symptoms. This experiment provides a window into the future of personalized precision medicine.