South Korea picked SendSquare, a blockchain startup, to build a data registry platform for diabetes research. The National IT Industry Promotion Agency (NIPA) is backing the project as part of a broad
South Korea picked SendSquare, a blockchain startup, to build a data registry platform for diabetes research. The National IT Industry Promotion Agency (NIPA) is backing the project as part of a broader push to strengthen the country's medical data infrastructure.
NIPA allocated about three million dollars this year to blockchain initiatives. The government selected SendSquare after the company's data collection tool earned recognition as an outstanding project in a previous government competition.
South Korea has more than 3.6 million people with diabetes. Researchers need access to reliable clinical information, but the current system isn't meeting that need. "Even though medical data research is essential in the field, it is not active enough because of insufficient data dissemination and some unreliable data," NIPA said in its announcement.
SendSquare will work with KyungHee University Medical Centre to build out the platform. The two teams plan to analyze nine years of diabetes patient records. "Storing and collaborating work across a large volume of data using centralised services has proven unwieldy and subject to issues of data loss, duplication and manipulation," Professor Suk Chon from the medical centre said. "Sendsquare's blockchain can help us to solve data storage problems, and in the long term help diabetes sufferers nationally," he added.
The system uses two separate blockchains. The private chain holds sensitive patient information with restricted access. The startup will pseudonymize, organize, and periodically update records to protect privacy while maintaining data quality. The public chain tracks when data changes, creating a permanent record that prevents tampering.
SendSquare estimates the platform could save the medical industry up to four million dollars compared to existing approaches to clinical research data management. The combined system will handle profiling, extraction, visualization, and documentation of medical records, improving efficiency and the insights researchers draw from the data.
