The vendors have discovered that the distributed ledger technology was faster enough and efficient. At the same time, it helps to maintain all the necessary privacy and security.
Both matching patients and clinical trials was a major challenge for everyone in the pharm critical companies and hospitals. Hence the move is coming from ConsenSys health and Intel to combine blockchain and AI.
Finding the right match based on certain health records demographics is difficult and time taking; it costs a lot and, at the same time, can slow down the clinical trials. This is one of the major reasons why trials fail. This further slows down the progress in the advancement of new medical treatments.,
Nearly 50% of cancer patients want to get involved in clinical trials. However, only 5% can do so. This limited access is quite cumbersome and obstructs the path of scientific improvements in treatments for future patients.
At ConsenSys Health, they are focusing on a new way to approach these concerns. They can keep the data safe and private at that place. Also, they have made it possible with a combination of the familiarity of technology- blockchain, AI, and privacy-preserving software and hardware.
They are working with Intel to align the next generation Intel SGX hardware for better confidential computing with their blockchain system. Also, it will help them to solve a variety of problems in the healthcare and life sciences.
It will enable faster and cheaper trails. Moreover, it will offer better access and inclusion for patients. It will result in a more robust advancement of new treatments.
ConsenSys worked directly with the team of Intel with synthetic health data. They have compared the latest version of intel SGX in Ice lake to their version. It has increased the enclave size and data processing. the new version is allowing for a faster and better data processing
ConsenSys Health has learned that this privacy-preserving approach is much faster and also maintains necessary security. They can use it for the host of potential use cases related to clinical trials.