Skip to main content
Premium Trial:

Request an Annual Quote

Nebula Genomics, Longenesis Seek to Legitimize 'Life Data Economics'


CHICAGO (GenomeWeb) – Last month, Nebula Genomics, a company cofounded by Harvard Medical School geneticist George Church, signed a partnership with Hong Kong startup Longenesis. Among their goals is to legitimize a new field they dubbed "life data economics."

The plan is to apply artificial intelligence and blockchain technology to build a secure platform for individuals and biobanks alike to store, manage, control, and sell access to genomic, laboratory, and other health data. To establish this data marketplace, they will issue a cryptocurrency backed by the value of the data.

"For example, individual people will be able to use a cryptocurrency to buy sequencing at our facilities," explained Nebula Genomics Chief Security Officer and Cofounder Dennis Grishin. "At a later stage, we would like to build out our platform [to support] third-party applications" that could be sold to users of the new, yet-unnamed network.

Grishin said that the partnership would address his feeling that sequencing and analytics — and, by extension, precision medicine — remain underutilized.

"Generally, genetic testing, whether it's genotyping or sequencing, hasn't really taken off. This is something that [Church] has been trying to popularize for over a decade," Grishin said.

"Our vision is that essentially every person should sequence his or her personal genome. We know that we will not only find interesting [genealogical] information from it like Ancestry, but it will also be very useful in regards to personal health," he explained.

Church has long believed that genomics would become routine and that patients would be clamoring for it as the price of sequencing genomes drops. Now, sequencing has fallen below the $1,000 barrier. "That's what many people spend on their phones," Grishin noted. "But people don't spend it on sequencing their personal genomes, which, if you think about it, is something much more important."

The $1,000 price point is still prohibitive for many, though.

"In fact, we believe now that the price not only needs to go toward zero, it needs to be almost net positive for people to sequence their genome," Grishin said. "That's what we're trying to accomplish with Nebula, enable people to actually profit from sharing their genomic data."

Alex Zhavoronkov, CEO of Insilico Medicine and CSO of Longenesis, said that accurate AI requires much more data than is currently available.

"You really need to have millions of datasets, not thousands. This hunger for data can be only satisfied by making the data a net positive for the people submitting the data," he said. "You need to provide a useful resource to the people and, at the same time, maybe pay them for the data."

Grishin said, however, that internal research at Nebula has found that people are increasingly concerned about the privacy of their genomic data, particularly about the risk that employers and health insurers could discriminate against them based on genetic predisposition to certain medical conditions. In the US, the Genetic Information Nondiscrimination Act (GINA) does restrict payors and employers from making coverage and employment decisions based on a person's genetic risk factors, however.

"What we are trying to do at Nebula is set a much higher standard for genomic data protection. Essentially, we don't want to take ownership of people's data, which is the business model of many other companies," Grishin said.

"Instead, we just enable people to remain owners of their data and manage completely who has access to their data … and when they do share it, enable them to do it in a way that is very secure and that is very transparent. That essentially ensures that their data is not misused."

This has become more important in light of the Facebook-Cambridge Analytica privacy scandal and with the May 25 advent of the General Data Protection Regulation in the European Union. "It's a matter of time until some kind of big genomic database gets misused in a similar way," Grishin said. "It will be much, much worse than this Facebook thing," he predicted.

"We are trying to build a system before that happens that wouldn't allow this to happen, that's essentially extremely decentralized, that enables every individual to just take care of their own personal data."

That is where blockchain and Longenesis come in. "The blockchain is a perfect tool for us to decentralize data ownership and at the same time also democratize it by allowing people to remain owners of their data," Grishin said.

Longenesis, a blockchain and artificial intelligence company, is a joint venture between AI technology vendor Insilico Medicine and cryptocurrency miner Bitfury. Zhavoronkov said that the partnership came together "serendipitously" at the 2017 JP Morgan Healthcare Conference.

"When we met [Bitfury] at JP Morgan, they were talking to a few pharma companies about pilots," Zhavoronkov recalled. Insilico was able to add a level of identity security and accuracy that Bitfury needed to work in life sciences, he explained. 

Additionally, the datasets need to be diverse to create the case for "life data economics," Zhavoronkov said. "The partnership with Nebula allows us to look at all of the data types and combine those data types."

Historically, phenotypic data, transcriptomes, and proteomes were more actionable to Zhavoronkov than genomes. "Before we started collaborating with Nebula, I did not [see] any value in genomic data," he said.

"But, combined, those datasets present a really unique opportunity to look into the past and look into the future and also get actionable insights into the various markers and targets. Combined with genomic information, that's really a gold mine," Zhavoronkov explained, that helps researchers get to root causes of disease.

The field of life data economics — plus associated terms the partners coined, "macrodataeconmics" and "microdataeconomics" — stems from work done by Insilico and Bitfury.

Microdataeconomics is about an individual's data, Zhavoronkov explained. The macro complement is focused on populations. "We combine the various data types to assess their combination value," Zhavoronkov said of the latter.

"We want to create the time value of data, so if you collect data over time consistently, it becomes more valuable, like a good wine," he said. That would combine with an event such as a cancer diagnosis. "The payout from this data type might be substantial. It might be more than it takes to treat that cancer," he said.

"For example, nobody I know has dynamic data even for self-use," Zhavoronkov continued. Facebook or other social media platforms might provide some life history, he suggested, "but there are no consistent, high-resolution pictures of anybody. There are some datasets online," but they might only contain a couple of months of daily snapshots of people's lives.

"If you had a dataset of, let's say, 10,000 people with 10,000 pictures, and you've got a combination of value of these datasets with, let's say, blood tests and transcriptomes, you could get a very valuable dataset that could be worth billions of dollars," Zhavoronkov said.

He also mentioned the concept of quality-adjusted life years (QALY) that various data points could generate. "In this context, you would be able to formulate the value of data from the healthcare standpoint," Zhavoronkov said.

The price per QALY in the US is about $60,000, Zhavoronkov said, based on how much insurance companies are willing to pay. "You can actually assess the number of QALYs you generate from the various combinations and permutations of data types together," Zhavoronkov said.

The Nebula-Longenesis partnership wants to add to that the "volume value" of data. "If you have a very large number of people with the same datasets, up until a certain point, the value of that data increases, and then you start getting diminishing returns," Zhavoronkov explained. "That's a new field. Nobody has touched on that. It's not intuitive, but that's where we are."

Grishin said the partners will test the concept this summer in a pilot with an unnamed large pharmaceutical company. Researchers will pay people to have their genomes sequenced in return for access to the data. This also will help Nebula Genomics test its own blockchain-based network.

Other work over the next 12 months will involve scaling up the platform by integrating different data types and partnering with biobanks to add their data to the network. Grishin said that he wants to have "millions of data points" within a year.

"I think what many people underappreciate is how the genomic revolution is going to change the lives of many people and create a new, billion-dollar industry," Grishin said. It's comparable to how the internet changed the world in the 1990s. Genomic data will be "able to create powerful AI models to really understand human genetics and it will just completely revolutionize healthcare."