A new startup called Nebula Genomics has released a white paper on its website offering people a way to cash in on their own genomes. Customers would pay to have their genome sequenced, (under $1000) but in return, would receive ownership of the data generated from it, which could then be sold by the customer to companies such as pharmaceutical manufacturers. Furthermore, transactions would occur using blockchain technology used for secure valued transactions such as Bitcoin.
Interestingly, the new startup is headed by George Church of Human Genome Project fame. He, along with employees from another of his companies, Veritas Genetics, and other investors, are suggesting that the approach is the wave of the future. They point out that other companies, notably 23andMe, retain ownership of user data derived from spit swab genetic samples, leaving customers out of the proceeds when they sell the data to other companies.
Unfortunately, the number of people taking part in personal genome sequencing is low, the group claims, because of price and privacy issues. In order to best make use of genomic data, researchers need samples from a lot of people. That would reveal trends that are helpful in identifying currently unknown hereditary disease factors. The only way to get many more people involved, the group suggests, is by guaranteeing that their data will only go where they decide and by bringing the cost down—which they claim can only happen by allowing those who give samples to sell their data to companies working on large research efforts. Nebula Genomics, they claim, is in a position to make that happen.
Notably, buyers and sellers would use Nebula tokens as money. Those wishing to have their genome sequenced, for example, would buy a token, which they in turn could sell to another buyer, thereby recovering their initial expenditure. But, as with Bitcoin, the value of tokens can change depending on a variety of factors. And since the tokens can only be redeemed by purchasing someone's DNA data, their value will depend on the willingness of big companies to use them to pay for data.