he said. Services in the marketplace now enable an individual to obtain their genotype and distribute it to people who will interpret it and return the results via e-mail. “People who are frustrated are increasingly going to find these services and start using them” despite a lack of standards, site protections, and privacy.
Wilbanks also uploaded the genome file he received from 23andme into the Sage Bionetworks Synapse system, which is a self-contributed data repository for genomics research. The system, which includes an online informed-consent process, allows data scientists to conduct collaborative research on individual-level data that are provided in a standard format and have been cleared with respect to privacy protections.
With the computational and consent infrastructures in place, the last piece in the democratization of clinical research is something that begins to change the role of the individual, “so it’s not just ‘I’m a patient and I see my doctor x number of times a year.’ You can be a participant,” said Wilbanks. Bridge, which is the newest piece of the Sage system, demonstrates the power of this kind of model. It provides a means for people who have data about themselves to come together and commission researchers to build the computational disease models. For example, he said, “50 people with early-onset Parkinson’s could come in and say, ‘we’ve got genomics data, we’ve got all sorts of other omics data, we’ve got metabolic and molecular data, it’s in a standard format—$50,000 prize to the first person who builds a successful computational model.’”
Wilbanks proposed a simple set of standards to guide this kind of public-driven data sharing. First, he said, be honest with people. If people send their genomes to a shared system where data are at least moderately public, their privacy is unlikely to be permanently protected. Contributors of data need to know about the risks they face, but society should also have some tolerance for people who think the value of sharing their data is greater than the risks, such as those with a rare disease. Second, data should be reusable, which to Wilbanks meant computationally useful. Scans of paper records that patients have typically received from their doctors when requesting their medical records, for example, are not reusable. Finally, data should be portable so they can be shared among institutions, doctors, laboratories, and studies. When the control group from one study can also serve as a cohort control for another, “it begins to accelerate the system exponentially,” said Wilbanks.