Nebula Genomics, a Harvard Medical School startup has announced entering a research partnership with Longenesis from Hong Kong. The two companies will collaborate in a field they have dubbed “life data economics.” The two companies, which have a lot of experience in blockchain technology and artificial intelligence in the medical field, will jointly develop a platform used to store and exchange genomic data.
The use of blockchain technology and artificial intelligence
Both Nebula Genomics and Longenesis will apply blockchain technology and artificial intelligence to develop a platform that will allow biobanks and people to safely store, manage as well as easily access genomic plus other forms of heath data. Health researchers will be able to pay in order to access a secure source of data.
Having a single database
Professor George Church, the Co-founder of Nebula Genomics said that the company is opening a window for people and large providers of data to store their genomic data on the platform, a move that the company says will be like an incentive to generation of genomic data.
This way, the company says it will be able to collect all the information on a single database where it can be securely and conveniently accessed by researchers. This simply means that the company will create a large market place that will establish and efficient and equitable economy for genomic data.
Longenesis is a product of a partnership between Bitfury Group, a blockchain technology company and Insilico Medicine, an Artificial Intelligence company offers the same online environment which focuses on longitudinal health data as opposed to genomics. Church says that the two companies’ platform will work in complementarity to each other.
Both companies have indicated that their technologies will explore and establish two sectors, microdataeconomics and microdataeconomics. Microdataeconomics entails the study of the value attached to life data which is used for drug discovery and development. On the other hand, microdataeconomics is the study of the value attached to life data which is used to establish trends in human health like genomics and electronic health records.
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