ENABLING SAFE USE OF SENSITIVE HEALTH DATA: NEXT-GENERATION ANONYMIZATION
AI ENHANCED QUALITY – BROADER USABILITY – MAXIMISING DATA VALUE
The VEIL.AI Anonymization Engine solves health data privacy problems. Utilize high-quality, record-level anonymized and synthetic health data.
Personal health data is very valuable and can also be used for research, innovation and development. However, secondary use of health data is only possible if the data is of high quality and privacy protection can be secured.
Introducing the VEIL.AI Anonymization Engine, an AI-based solution that transforms sensitive health data into high-quality, record-level anonymized and synthetic data that is GDPR- and HIPAA compliant. This offers great new opportunities to utilize health data for Pharma and MedTech companies, Hospitals and Researchers, and all organizations that want to use health data securely for secondary use purposes.
Did you know that there is not only one way to anonymize a dataset? There are actually an astronomical number of ways to do it. So how can you get the best anonymization results for your specific use case?
During our years of working with health data de-identification we realized that the quality of anonymized data was not ideal. Old state-of-the-art anonymization methods lose a significant part of the most interesting and relevant data in the anonymization process. Therefore, you cannot draw the same conclusions from such a dataset compared to the original data.
This is why we created next-generation anonymization.
With the VEIL.AI Anonymization Engine you can control and customize the anonymization process to optimize quality. Artificial Intelligence searches for the optimal anonymization result for your use case. And you can draw the same conclusions from the next-generation anonymized dataset as from the original data.
We specialize in health data anonymization, synthetic data and pseudonymization services. Our unique (patented) technology helps life science and healthcare stakeholders utilize sensitive data in ways that were not possible before.
Combine and anonymize sensitive data from multiple parties in real-time with unmatched scalability. Record-level data anonymized with VEIL.AI outperforms the competition in utility, quality, and performance.
Utilize synthetic data to gain real world insights or use synthetic data for realistic training and testing purposes. Hospitals and pharma companies can use synthetic data for e.g. AI algorithm development.
Pseudonymization and consent management
Achieve compliance (GDPR, HIPAA, etc.) with sensitive data. We also offer pseudonymization, data minimization and consent management services for, for example, hospitals and biobanks.
Data strategies and Risk assessment
Crystallize your plans to utilize anonymization and synthetic data in your data strategy. Understand the privacy risks involved in your data-driven business.
What do our customers say?
Expert Clinical Data Scientist
This is a significant achievement. In our study, we could draw the same conclusions from anonymized data as from traditional pseudonymized, individual-level research data.
Jukka Partanen, Professor
Research & Development
Finnish Red Cross
We create potential for saving lives
“The Finnish Red Cross Blood Service is the nationwide blood service provider in Finland, recruiting blood donors, organizing blood donation, collecting blood and testing the donated blood. The Blood Service uses the donated blood to make cellular blood products which is then delivered to hospitals for use in treating patients. It also operates a Stem Cell Registry.
We have chosen VEIL.AI’s CORE service as part of our IT architecture to address our pseudonymization and consent management needs. We are very satisfied with the service and flexible development possibilities.”
VEIL.AI makes sensitive data safe to use
What are the main differences between sensitive data, pseudonymized data, anonymized data and synthetic data?
Since GDPR does not apply to anonymized or synthetic data, using these methods opens up new possibilities for using health data in novel ways.
Thanks to VEIL.AI’s unique technology, you can now get better access to health data and easily combine, analyze and share data in more use cases than were possible before.
Why do our customers and partners want to collaborate with us?
Solutions for Pharma companies, Hospitals, Biobanks and all organizations handling sensitive data.
"We want to get better access to health data"
VEIL.AI’s advanced anonymization enables access to sensitive data. You can utilize data faster, more easily and more securely.
“We want to produce more Real World Evidence”
The importance of Real World Evidence is increasing. We can help you to, for example, improve your capability to create and utilize RWE.
“We want to utilize health data for secondary uses”
Anonymized datasets are not restricted by GDPR / HIPAA and can be utilized for research, development and innovation.
“We want to combine health data from different countries and sites”
Anonymized data allows for easier transfer and larger data set generation. Utilize pooled data for the study of rare diseases, rare endpoints and events.
“We want to reduce the costs of clinical trials”
Advanced anonymized data is required if you are planning to reduce the cost and increase the speed of clinical trials. Your RCT data can be re-used and your data becomes more valuable.
“We want to increase evidence generation efficiency”
Good quality data is essential also in decentralized clinical trials. Let us help you increase your evidence generation process with better data for RWE and Predictive Evidence.
“We want to improve our data science capabilities”
Advanced anonymization can give more and better data, allowing your data scientists to increase the scope of their work and enabling new possibilities.
“We want to strengthen our data strategy”
Need a sparring partner or consultant to develop your organization’s processes and strategy concerning data anonymization?
“We want to collect data from wearables and IoT devices”
The VEIL.AI Anonymization Engine is the most effective solution to anonymize streamed accumulating data from wearables, Medical devices and IoT devices.
“We want to develop AI algorithms for better treatments”
In order to develop better treatments for patients, AI algorithms may be utilized. We specialize in creating synthetic data from health data.
“We want to enable better interoperability”
Value-based care requires sharing of data, for instance by interoperability. Advance anonymization can be a key tool in the data sharing needed for value-based care, and an alternative to federated architecture.
“We want a reliable pseudonymization and consent management solution”
We provide both ready-made and custom user solutions for biobanks and hospitals. In addition, flexible technical service is available.
Utilization of anonymization techniques to create an external control arm for clinical trial data
Download the research on "Utilization Of Anonymization Techniques To Create An External Control Arm For Clinical Trial Data"
“This is a significant achievement. In our study, we could draw the same conclusions from anonymized data as from traditional pseudonymized, individual-level research data.”
- Jussi Leinonen, Expert Clinical Data Scientist, Bayer
VEIL.AI designed a study together with our partners Bayer and MedEngine to compare the use of anonymized and pseudonymized Real-World Data (RWD) in creating external control arms (ECAs) for single-arm randomized controlled trials (RCTs) .
The study, published in BMC Medical Research Methodology, showed that one could draw the same conclusions from anonymized data as from traditional pseudonymized, individual-level research data.
Blog & News
Check out our latest blog and news. View all posts here.
VEIL.AI uses LUMI supercomputer to speed up development of next-generation anonymization technology for health data
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Next-generation anonymization of Real-World Data in clinical trials gives the same conclusions as pseudonymized data
Real-world data (RWD) gathered from daily healthcare practices is becoming more important in medical research, especially when studying questions ...
VEIL.AI to build next-generation anonymization and synthetic data capability for six European children’s hospitals’ ecosystem
VEIL.AI – the most experienced European health tech company in health data anonymization – has partnered with pediatric hospitals ...
Federated learning- what is it, and how does anonymization complement it?
Federated learning is a new technique that has been proposed as a solution to the issues of sensitive data ...
Expanding Secondary Use of Health Data: Benefits and Future Possibilities
As the digitalization of health data becomes more common, the healthcare industry is witnessing a shift towards data-driven decision-making. ...
What is the difference between ‘de-identified’ and ‘anonymized’ data?
Following the passage of the European General Data Protection Regulation (GDPR) in 2018, there has been much confusion between ...
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