Super Well-Being
By recording our mood and behaviors and pooling this data, together we can find the most effective ways to eliminate stress, anxiety, and depression. Gamification can help us maintain the behaviors necessary to maximize our health and happiness.
Super Intelligence
The next frontier of crowd-sourced research will be to determine the lifestyle behaviors, diets, and nutritional supplements that most effectively enhance cognition. The world is filled with problems that need to be solved. Our minds need to be operating at full capacity if we expect to meet these challenges.
Super Longevity
Over 100,000 people die every day of diseases that will eventually be cured. At the current pace of medical research, it is unlikely that these numbers will go down anytime soon. Fortunately, new technologies will enable us to dramatically accelerate the pace of this research through the power of crowd-sourcing.
AIM 1: Acquire, integrate, and normalize heterogeneous data from devices and applications
You can’t manage what you don’t measure.
The first step towards life improvement is tracking the relevant variables. Once you start gathering data, Quantimodo will enable you to effortlessly integrate data from disparate mobile apps, web apps, and devices! If you don’t see your favorite listed yet, we’re open to suggestions.
Challenge: To acquire, extract, transform, and normalize the countless unstandardized data export file formats and data structures and load them into a standardized structure that can be easily analyzed in order to derive clinical insight.
Approach: We will develop an application programming interface (API) for receiving data, a spreadsheet upload/import module, a connector framework to pull data from existing third party API’s, and software development kits (SDK’s).
Impact: The API connector framework will allow ongoing regular import of user data after a single user authorization. SDK’s will enable developers to implement easy automatic sharing options in their applications. An increase in the quantity of data will produce a proportional increase the number of clinical discoveries made.
AIM 2: Calculate the personalized correlation between every quantifiable factor and symptom severity and determine optimal daily values of these factors for each user
Challenge: To quantify the effectiveness of treatments for specific individuals, reveal hidden factors exacerbating their illness, and determine personalized optimal daily values for these factors.
Approach: We will develop time-series data mining algorithms to quantify correlations between every combination of variables for variables for a given subject. We will also design algorithms capable of determining the minimum quantities of nutrient intake, sleep, exercise, medications, and other factors necessary to minimize symptom severity.
Impact: This will mitigate the incidence of chronic illness by informing the user of symptom triggers, such as dietary sensitivities to be avoided. This will also assist patients and clinicians in assessing the effectiveness of treatments despite the hundreds of uncontrollable variables in any prescriptive experiment.
AIM 3: Establish a research commons to anonymously pool data in stratified user groups and share discoveries
Challenge: To allow users to publish their findings and reduce error in correlational analysis by increasing user sample size through grouping data from relatively homogenous groups of users.
Approach: We will expand the WordPress content management system and the QuantiModo Connect to serve as a platform where anyone can share, access, and analyze anonymous data and publish studies. We will also enable grouping of data among relatively homogenous groups of users stratified by their environmentomic, microbiomic, demographic, genomic and/or diseasomic profiles.
Impact: Clinicians and those suffering from chronic conditions will have access to personalized effectiveness rates of treatments and the percent likelihood of root causes.
This work will usher in an era of personalized preventative medicine through crowdsourced clinical research by providing (a) a new secure platform capable of aggregating massive amounts of heterogeneous life-tracking data, (b) a tool to help clinicians and those suffering from chronic conditions determine personalized effectiveness rates of treatments and the percent likelihood of root causes, and (c) the ability to run and publish large-scale observational research studies in a matter of minutes on stratified user groups.