Healthcare · Research
Federated Clinical Trials
Multi-site clinical trials require sharing sensitive patient data across institutions, raising privacy and sovereignty concerns.
The challenge
What stands in the way
Multi-site clinical trials require sharing sensitive patient data across institutions, raising privacy and sovereignty concerns.
The solution
How Scrydon solves it
Federated learning enables AI models to train across trial sites without raw data ever leaving each institution's secure environment.
Built on
In practice
How this plays out
A multi-site trial needs a large enough patient population to reach statistical significance, but pooling raw patient data across institutions raises exactly the privacy and sovereignty concerns that can stall a trial for months of legal review.
Data Spaces let each site keep its own patient data in place while contributing to federated model training, so the trial reaches the population it needs without a single record ever leaving the institution that holds it — accelerating development without a data-sharing agreement standing in the way.
The result
- Accelerated drug development with full compliance to data protection regulations.
See how this works for your organisation
Let's map this healthcare use case onto your environment, your data and your sovereignty requirements.
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