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Safely productize your healthcare data

Healthcare data is highly sensitive, and subject to strict regulations. Consequently, making it accessible for wider use can be challenging. However, if the accessibility to diverse, relevant patient and clinical data is hindered, it can significantly limit the progress of Healthcare AI. Apheris removes these constraints by offering a secure way to make sensitive data readily available for AI/ML applications without necessitating centralization or direct data sharing.

Make healthcare data accessible without sharing

Apheris provides the gateway to federated learning and is enabling collaboration across academia, hospital networks, researchers, and industry. Providing governed, private, and secure computational access to sensitive data for ML and analytics across boundaries, you stay in control, manage, and trace every computation.

Enable federated learning

Apheris helps to curate and standardize available and future data sets to ensure interoperability and enables access to longitudinal data that is complete, standardized, and prospective.

Private & secure

Apheris leverages different PETs with the highest level of precision to ensure only privacy-preserving results are returned to the user. Robust security controls ensure only permitted computations are run on data.

Computational access governance

Connect data while maintaining full control of your data. Define who can access your data and for purpose down to the computational level. Continuously monitor and audit the data you provide computational access to.

No need to move data

Apheris is the architectural backbone for health data in research networks around the globe. The Apheris Compute Gateway gives organizations and researchers the possibility to share insights, without moving data and while respecting data ownership and privacy.

Private data stays private

Health data is highly sensitive, and subject to strict regulations and privacy rights. Apheris allows you to control who has computational access to which data, define what jobs can run for what purpose, and ensures only permitted jobs run. Only privacy-preserving results are shared and with audit capabilities, you stay compliant with all regulations.

Certifiably secure

Connect and scale

Connect multiple gateways to enable federated learning over data that crosses organizational and geographical boundaries. Enable new use cases while reducing cost and increasing speed of providing data for machine learning and analytics.

Use Apheris to...

Work with life sciences and pharma companies and enable them granular computational access to real-world data for AI, ML and analytics use cases.

Establish federated trusted research environments

Accelerate scientific breakthroughs by making data securely accessible while ensuring all compliance obligations.

Commercialize your data assets

Make data available to your pharma and life sciences customers. Enable them with federated machine learning and optimize the model training process.

Cross-border data analysis

Work collaboratively across borders while ensuring compliance with privacy regulation and residency requirements. Integrate Apheris into your workflows and ensure that data stays protected and never moves across borders.

Build federated real-world data networks

Engage in data collaborations across private and public institutions.

What customers are saying about Apheris

Healthcare

"We have the capabilities to interrogate our rich dataset, but we lack the governance and privacy piece to enable our customers to do this on EU data. This is what Apheris helps solve for us."

Product Director Data Aggregator

Resources

Case Study

Enabling federated research for life sciences

A leading data aggregator in healthcare research partnered with Apheris to provide life sciences customers with granular access to patient data while ensuring GDPR compliance. Apheris enabled fully federated machine learning, optimizing the model training process and enhancing customer satisfaction by addressing long-standing GDPR issues. This partnership illustrates Apheris's potential to unlock data assets securely and efficiently.

Article

Enabling IP-Preserving Computations on Sensitive Data

Machine learning and AI needs domain-specific data to be trained for its various use cases. Often this data is sensitive and falls under various privacy regulations. In this article we will introduce the Apheris Compute Gateway as a solution for contributing sensitive data to ML projects.

White Paper

Privacy and Security Whitepaper

Privacy and security considerations are an important part of adopting a federated infrastructure for machine learning and analytics. This whitepaper outlines the various security techniques and privacy controls used by Apheris to safely collaborate and build data applications and AI across organizational and geographical boundaries.

Case Study

Enabling federated research for life sciences

A leading data aggregator in healthcare research partnered with Apheris to provide life sciences customers with granular access to patient data while ensuring GDPR compliance. Apheris enabled fully federated machine learning, optimizing the model training process and enhancing customer satisfaction by addressing long-standing GDPR issues. This partnership illustrates Apheris's potential to unlock data assets securely and efficiently.

Ready to productize your sensitive data?

Discuss your needs for governed, secure, private computational access to data with one of our experts.