In a new direction for clinical trials, and in reflection of how much of the world has moved on-line, two online tools that aim to recruit volunteers to freely share their genetic and health data with researchers and Facebook friends have recently been launched.
The first of the two platforms is called the Open Humans Network
. This platform opened with with three starter projects. The aim, as captured in the titled "Open", is that clinical data collected from participating volunteers will be made available to any interested researcher, not just the leader of each project. Thus, unlike traditional medical studies, each sample will be tied to the name of the volunteer who provided it, allowing researchers unaffiliated with the initial project to contact participants for follow-up studies. Open Humans participants must pass a test acknowledging the risks of enrolling in the network, including potential hacking of their medical information.
The project director Jason Bobe told Reuters
: “You become a richer resource if your data are shared among as many scientists as possible.”
The three starter projects are:
American Gut, led by Rob Knight of the University of California, San Diego, which will probe the relationship between the gut microbiome and disease.
GoViral, led by Rumi Chunara of the New York University Polytechnic School of Engineering, which gathers information about viruses causing respiratory illness.
Personal Genome Project, led by George Church of Harvard, which examines human genomes for trait and disease markers.
The second online project is called Genes for Good
. This project, according to BuzzFeed News
, seeks to recruit volunteers through a free Facebook app. Selected participants will be asked to send a tube of their spit to the University of Michigan for genetic analysis. The app asks participants about their health and habits and compares the answers to those of other users. It also provides a limited analysis of the roughly 500,000 genetic markers the scientists will screen, such as an interpretation of the user’s ancestry.