How to Ensure Data Security with OpenSimplify: A Comprehensive Guide
- Josh Wright
- Jun 16
- 2 min read

In the era of digital clinical research, data security is not just a feature, it's a necessity. With sensitive health records, patient identifiers, and high-stakes analyses on the line, any compromise can lead to reputational and regulatory damage. That’s why OpenSimplify is designed with security at its core, giving users confidence that their data is safe at every step.
Here’s how OpenSimplify ensures data protection while delivering world-class clinical research analyses in the cloud.
1. HIPAA-Aligned Infrastructure
OpenSimplify is built on AWS with a Business Associate Agreement (BAA) in place, meaning the infrastructure follows HIPAA-compliant security standards. All storage, computation, and backups are managed through secured AWS environments that support encryption, access control, and audit trails.
2. Encrypted Data at Rest and In Transit
Whether you're uploading patient data for analysis or saving multivariable models, your files are encrypted:
At rest: All files are stored in AWS S3 with server-side encryption enabled.
In transit: TLS/SSL protocols secure your data when it's moving between your device and the server.
3. User-Level Access Control
Each OpenSimplify project has built-in role management. Whether you’re the lead investigator or a collaborator:
Users can only view or modify what they’re permitted to.
Project sharing is done via username-based permissions, not open links.
This minimizes accidental data exposure and keeps the right people in control.
4. Temporary & De-Identified Processing
OpenSimplify is structured to encourage good data practices:
Data is not stored permanently unless saved into a defined project by the user.
Users are guided to remove PII (personally identifiable information) before uploading.
Temporary uploads for quick analysis are automatically purged after sessions.
5. Activity Isolation by Project
Each research project exists in a siloed environment. Saved analyses, uploaded files, comments, and tasks are tied specifically to your selected project. This ensures:
No cross-project contamination
Clear data governance per study
6. Built-In Best Practices Reminders
OpenSimplify doesn’t just enable secure workflows, it encourages them. Throughout the app, users see reminders like:
“Ensure your dataset contains no identifiable patient information.”This gentle but consistent guidance helps prevent compliance issues before they start.
7. Your Data, Your Control
Users can delete any uploaded files, saved analyses, or entire projects at any time. OpenSimplify gives full control back to the researcher, nothing is locked or hidden.
Conclusion: Secure by Design, Powerful by Default
Security shouldn’t be an afterthought, it should be baked into the product from the start. With OpenSimplify, clinical researchers get a modern analytics platform that balances novel functionality with rigorous protection.
So you can focus on advancing science, not managing security risks.
Ready to analyze safely? Visit OpenSimplify to experience secure, intuitive clinical research processing and analyses today.
For further information and data processing and analyses solutions, explore our OpenSimplify.
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