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Affecting 200 million people worldwide and claiming 18 million lives annually, cardiovascular disease (CVD) is a critical global health challenge. iCARE4CVD aims to change that. Led by Novo Nordisk and Maastricht University, the iCARE4CVD consortium consists of 34 leading healthcare organizations that aim to save millions of lives by using artificial intelligence (AI) to improve early detection and personalize care for CVD. The consortium aims to create the largest CVD database as well as develop and train AI models for improving early diagnosis, risk assessment, and treatment effectiveness — ultimately enhancing patient quality of life and global CVD outcomes.
The challenge
To train its AI models, the iCARE4CVD consortium requires sensitive, high-quality patient data. This results in challenges to patient privacy protection as well as compliance with international health data regulations.
Additionally, there is an inherent need to safeguard the competitive advantages companies create for themselves with their clinical trials and proprietary data.
For these reasons, iCARE4CVD needed a platform that fulfilled three essential functions: facilitating data encryption, preserving the privacy of any results generated, and machine learning analysis.
The solution
Because of their unique ability to maintain absolute data privacy, while remaining flexible to research workflows, iCARE4CVD is using Decentriq’s data clean rooms to enable the data collaboration in the consortium.
The technology powering Decentriq is what enables the consortium to perform patient-level data analysis without revealing sensitive information: Using confidential computing as a basis, the data clean rooms allow participants to analyze data while it remains encrypted. Additional privacy-enhancing technologies and control mechanisms built into the data clean rooms allow data custodians to control exactly how their data is used beforehand, while assuring that analysts can only extract privacy-preserving results of models and computations — never raw data itself. Additionally, Decentriq as the operator of the platform can also never view or access the data. These measures guarantee that consortium data analysts can perform their usual tasks compliantly, without the risk of inadvertently leaking sensitive information from the data clean room environment.
Decentriq's cloud-based SaaS model drastically simplified the onboarding process for iCARE4CVD partners. As there is no change needed in the partners’ IT infrastructures, partners can simply connect to the platform via secure, web-based connections and deploy their already existing models without custom alterations. Additionally, integration capabilities and privacy-enhancing technology features accommodate current workflows to build the new AI models, while addressing organizational requirements.
The results
Decentriq's implementation has dramatically improved the pace in which CVD research and development could be conducted in the consortium, reducing the data analysis IT setup time from 24 months to six.
As the core analytics platform for the iCARE4CVD consortium, Decentriq significantly improves efficiency and speed of data acquisition for AI model development and deployment. This ensures that research is faster and better translated into clinical practice, improving patient outcomes, and saving lives.
Decentriq plays a pivotal role as a consortium partner by offering continuous support and training, coordinating work groups for feedback, and providing consistent platform upgrades. Future phases will see the integration of necessary architectural additions based on partners’ workflows and requirements.
In addition to improving patient outcomes, the use of data clean rooms will foster sustainability in CVD research by optimizing resource usage, reducing unnecessary medical interventions, safeguarding data privacy, and promoting ethical data handling.
Decentriq has a well-developed, interoperable, and ready-to-use solution for consortiums, in line with EHDS efforts. This allows consortiums to be much more efficient and partners to focus on ongoing research instead of having to dedicate resources to building a new platform for every project.
For more information on how your healthcare or life sciences organization can benefit from privacy-preserving data collaborations, read our “Data clean rooms for real-world healthcare data” whitepaper.
Whitepaper: Unlock the value of real-world healthcare data with confidential data clean rooms
As the amount of healthcare data from real-world settings grows, how can care providers and life sciences companies use this data to advance research and treatment while protecting sensitive patient information?
![Key visual for unlocking real-world data with data clean rooms](https://cdn.prod.website-files.com/64ff7fc0a1fbc8217fee67f7/6565bebde1d253b3a1bf9441_Screenshot%202023-10-31%20at%2014.50.08.jpeg)
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