Verseon adopts FHEnom for AI to secure clinical research data

Verseon has selected DataKrypto's FHEnom for AI to secure the continuous encryption of AI-managed medical research and clinical trial data.

Verseon, which focuses on the development of new treatments for major human diseases, relies heavily on artificial intelligence (AI) in its drug discovery and clinical trial endeavours. The sensitive nature of the data involved has prompted Verseon to move towards more robust data protection methods, particularly as regulatory requirements for data privacy in medical research continue to intensify.

The adoption of DataKrypto's FHEnom for AI aims to ensure that all AI datasets and proprietary models used by Verseon remain encrypted at all times, both during training and inference. This approach is designed to prevent unauthorised access and reduce the risk of malicious exploitation.

David Kita, Chief Scientific Officer of Verseon, commented on the integration of FHEnom for AI within their workflow.

"DataKrypto's FHEnom for AI gives us a secure, continuously encrypted solution for our AI training, fine-tuning, and real-world usage," said David Kita, CSO of Verseon. "With implementation taking just hours, the solution combines security with convenience and speed, allowing us to focus on our core activities."

Continuous data encryption is seen as integral to Verseon's operations, as the company handles significant volumes of clinical trial data and develops proprietary AI models critical to drug discovery. Ensuring security throughout the entire lifecycle of the data-from initial research to real-world applications-is key to meeting compliance requirements and maintaining operational trust.

Ravi Srivatsav, Chief Executive Officer of DataKrypto, explained how the FHEnom for AI solution addresses the specific challenges faced by companies such as Verseon.

"Verseon's mission-critical drug discovery and development work is reliant on its ability to maintain continuous protection of its clinical trial data and proprietary AI models," said Ravi Srivatsav, CEO of DataKrypto. "FHEnom for AI fills the encryption gap by enabling AI training and processing without having to decrypt data, which potentially exposes it to malicious use. We are proud to provide the first solution that gives companies like Verseon confidence and peace of mind with their AI implementations, knowing that their data is always secure."

Data privacy and AI security

FHEnom for AI uses a zero-knowledge framework that is specifically designed to be compliant with AI processes. The technology supports both custom-tuned open-source models for enterprise deployment and proprietary models, aiming to ensure data security across varied AI applications. This approach promises to guard against external threats such as malicious misuse, adversarial interference, and potential data leaks, while also securing intellectual property.

The solution is targeted at enterprises that deploy AI in sensitive fields and require assurance that both their data and their AI models remain confidential and resistant to manipulation. For companies like Verseon, where intellectual property is central to ongoing competitiveness and compliance standards are particularly strict, this type of seamless, continuously active encryption offers a new layer of operational assurance.

Clinical research applications

AI is increasingly playing a significant role in pharmaceutical research and clinical trials, supporting the analysis of large data sets and assisting in the identification of novel drug candidates. Verseon's use of DataKrypto's technology is intended to support these processes while ensuring compliance with national and international data protection standards.

The integration is promoted as a relatively fast process, with DataKrypto emphasising that the system can be deployed within hours and does not create external management overhead for the scientific staff involved. This is seen as an advantage in allowing research and development teams to keep their focus on drug discovery rather than data infrastructure and security logistics.

As the industry continues to adopt AI tools in increasing numbers for the investigation of diseases and novel treatment options, managing the delicate balance between operational speed, data usability, and full compliance with data privacy remains a key concern for all stakeholders.