South Korean biotech player Macrogen is partnering with Big Data company Bigster to create a blockchain platform for genomic data.
Macrogen, a South Korean biotechnology major providing gene sequencing solutions, announced on Monday a collaboration with Big Data venture Bigster to utilize blockchain for a medical platform that would help parties safely store and exchange gene data and other types of information.
Macrogen and Bigster aim to develop the platform by June 2019. The two companies will follow in the footsteps of Nebula Genomics, LunaDNA, and other entities that are currently leveraging the distributed ledger technology (DLT) for DNA data storage solutions.
Genomic data refers to the information about a person’s biological pattern, such as the DNA or the genome. Data storage and processing requires a high degree of security and privacy, which can be achieved with blockchain. In order to protect genomic data from hacks, security risks, and privacy infringement risks, the companies have to implement advanced cryptographic and non-cryptographic measures. Blockchain is known as one of the safest and most hack-resistant technologies. Besides, it allows parties to handle large amounts of data.
Macrogen plans to develop a platform that will operate a private blockchain, suggesting that participants will be entities such as pharmaceutical companies, hospitals, gene sequencing providers, and research institutes.
Macrogen CEO Yang Kap-seok commented:
“Despite its wide utility, gene data has been difficult to move around due to privacy protection issues and technological barriers. We hope that our upcoming blockchain-based platform will allow health care gene and medical Big Data to be circulated freely.”
In April, the biotech group acquired a research tool license to the CRISPR-Cas9 technology from the Broad Institute of MIT and Harvard, which would allow it to advance its gene treatment research and development.
In May, blockchain-oriented startup Shivom raised $32 million in its first stage of crowdfunding, getting a step closer to building its genomic data pool on DLT.