Unlock real-world data for healthcare innovations

Revolutionize patient care and drive advancements in treatment through compliant, secure data collaboration.

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Compliant analysis on patient data that stays confidential

Set research free from data silos while sensitive health data stays inaccessible and protected at all times. Compliance is enforced by market-leading privacy technologies built into our easy-to-use data collaboration platform.

Screenshot of Decentriq user interface highlighting synthetic data and python capabilities, and the availability of pharmacy data

Raw data is encrypted and inaccessible

The clean room encrypts the data at source with a key that only the data custodian can access. Only they can see the raw data — not even Decentriq or the cloud provider.

Screenshot of Decentriq interface showing the upload of encrypted data, highlighting that data the user owns is protected by a key under their control

Explore the dataset with synthetic data

Generate a synthetic dataset based on the original data. This gives analysts the freedom to explore while personally identifiable information stays protected.

Screenshot of the Decentriq interface highlighting anonymized gender and synthetic birth year within synthetic patient dataset

Approve and run analysis

Write Python, R, or SQL scripts and submit them for approval to run on restricted data. The dataset itself remains confidential and encrypted throughout.

Screenshot of the Decentriq platform highlighting a complex code snippet, the two users involved in the analysis, and a button to approve analysis.

Access results

Get access to the results of approved computations. Discover new insights to detect diseases early, inform treatment pathways, and develop new healthcare innovations.

Screenshot of the Decentriq platform highlighting results from the analysis: disease complication rates calculated from joined health datasets

Market-leading data privacy

Protect sensitive data with technology relied on by privacy-sensitive organizations including hospitals, banks, and even the Swiss Army.

Partner twice as fast

Set up collaborations quickly across organisation boundaries, with no infrastructure setup needed and built-in compliance guarantees.

Fits research workflows

Integrates easily with existing research processes, teams and tools. Flexible analysis in R, python and SQL

Decentriq’s unique solution gives us the ability to bring diverse datasets together for research while strictly preserving patient privacy. By facilitating secure analysis, their innovative approach holds the promise of improved patient outcomes and a more collaborative healthcare ecosystem.

Prof. Dr. med. Dirk Müller-Wieland
University Clinic RWTH Aachen

In the healthcare world, ease of use is key — and so is privacy. Decentriq’s unique, intuitive interface and privacy guarantees drastically simplify how we can approach healthcare partners. The straightforward UI makes it easier to explain how collaboration works, which helps build trust and a common understanding of what we can achieve. Decentriq worked hard to make things simple.

Bilal Husein
Data Analyst, Roche

Decentriq’s confidential computing technology brought the necessary flexibility to our yearly benchmarking study and upscaled confidentiality levels to the current requirements of our pharma customers.

Bart Bierinckx
Managing Partner, IM Associates (an IQVIA company)

By partnering with Decentriq, we can offer a transformative solution that addresses the long-standing challenge of collaborating on European RWD. It will open new avenues for privacy-centric health data research collaboration, power insights that advance patient health outcomes, and create ****new efficiencies in the healthcare system.

Jamie Blackport
Head of International, Datavant

Data collaborations between hospitals and external organizations happen frequently in the context of multiple sclerosis research. Data clean rooms make these easier, more secure and even open up new collaborations that were impossible to date.

Dr. Lil Meyer-Arndt
MD, Neuroimmunology

With limited resources, analyses gets backlogged. Using data clean rooms, we can collaborate and help institutions analyze the data, while they can be fully confident that the data is in their full control, and that no one else - neither Decentriq nor Roche - has access to the raw data itself.

Asad Preuss-Dodhy
Data Privacy Technologies and Digital Trust Program Lead, Roche

How secure data collaborations can drive advances in healthcare and treatment

Understand the full patient journey and measure outcomes

Especially for complex diagnoses, patients interact with multiple healthcare providers, pharmacies, and often devices and apps. In Decentriq, these data sources can be combined and analyzed — without revealing sensitive information — to create a full picture of treatment and outcomes. This can, for example, be used to assess the efficacy of new medications or digital interventions for reimbursement.

A venn-diagram graphic representing a collaboration between a pharmacy, payor, and a health app. At the intersection of the collaboration is Decentriq. The output is a table showing rate of adherence to treatment pathways.

Discover and assess novel biomarkers without sharing patient sample data

To discover and develop novel biomarkers — or to validate it for use in a new population — pharmaceutical companies need to be able to test their biomarker models on very large patient datasets. In Decentriq, they can run this analysis on multi-site and multi-modal data without directly accessing patient data. Their proprietary models remain confidential as well.

A venn-diagram graphic representing a collaboration between a pharma company and a hospital. At the intersection of the collaboration is Decentriq. The output is novel biomarkers.

Develop and deploy tools to detect and treat diseases earlier

Diagnostics tools can support healthcare professionals immensely, especially in rare disease detection and assisting decision-making. With Decentriq, life sciences companies can train AI assistants and other complex diagnostic models on disparate patient data while both the data itself, and the model, stay completely confidential. They can also deploy these tools across sites without needing to set up new infrastructure.

A venn-diagram graphic representing a collaboration between a hospital, a pharma company and a health app. Decentriq is at the intersection of the collaboration. The output is a table showing improved risk prediction for different patients.

Frequently asked questions

Decentriq enables organizations to make use of siloed healthcare data to improve patient care in a privacy preserving manner. Our platform provides you and your partners with a flexible infrastructure to analyze and generate results without the need to ever share any data and bring better and faster scientific innovation to patients.

Decentriq's data clean rooms facilitate a wide range of collaboration scenarios, from small-scale one-to-one partnerships to collaborative ecosystems involving multiple partners working together on data. Read more about how Roche is using Decentriq in our blog post.

Whether your aim is to identify novel biomarkers on the basis of sensitive data, to analyze data from multiple sites and partners, or to train sensitive AI/ML models, our data clean rooms enable flexible, privacy-preserving analytics while decreasing overhead costs.

Do you have a specific use case in mind you would like to explore? Get in touch with us.

Most methods for sharing data involve just that — sharing your data and hoping it is in good hands or that it is used according to your wishes. Decentriq enables meaningful insight generation from collaborations, without data ever having to be shared. We also guarantee that no one — not even Decentriq — can see the raw data you’re collaborating on.

Using confidential computing combined with synthetic data generation, output privacy measures and strict data access controls, our platform enforces GDPR-compliant analysis, and provides proof in the form of an immutable audit log. For more information on why you need more than standard encryption, read our blog post: Standard encryption is not all you need.

The Decentriq platform does not require any additional or special infrastructure from any users and supports seamless integrations with currently existing workflows.

On the data custodian side, files just need to be connected to the platform and they will be encrypted at source. And computations need to be approved in line with the purpose of the collaboration.

Data analysts can freely define code using supported languages (SQL, R, or Python) in the data clean room. This enables them to conduct sophisticated modeling and data science tasks on datasets while ensuring privacy and security.

Privacy-enhancing technologies can be divided into two segments: Input privacy and output privacy. At Decentriq, we do not believe in a single solution for privacy technology, which is why our data clean rooms employ multiple input and output privacy enhancing technologies such as confidential computing, K-anonymity (aggression), differential privacy, and synthetic data.

Data encryption at rest and in transit have been the standard for decades. However, this still leaves data vulnerable while it is in use (being analyzed). Decentriq leverages confidential computing technology to ensure your data remains encrypted in use, making it the first analytics platform that encrypts your data throughout its entire lifecycle.

Sensitive data stays confidential, and under your control — enforced by technology.

Built with the most advanced encryption and privacy technologies on the market, Decentriq keeps sensitive data completely inaccessible even while enabling deep analysis. Decentriq cannot access your data, only you hold the key.

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See how healthcare and life sciences organizations are using Decentriq

Do more with sensitive data

We’re here to help you tackle your data collaboration challenges. Contact us today to learn more or schedule a demo.

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