DNV to Ensure Quality Assurance of Synthetic Data Use in Healthcare
A new project called SYNTHIA, funded by the European Union, is set to speed up the use of artificial intelligence (AI) in the healthcare industry. The project aims to solve a big challenge in healthcare research: the need for high-quality data while keeping patient information private. To do this, SYNTHIA will use generative AI to create “synthetic data”—a type of data that looks and acts like real patient data but doesn’t reveal any personal information.
What is SYNTHIA?
SYNTHIA is a large-scale research project that includes 32 partners from 16 countries across Europe. This group includes big names like Novo Nordisk, GE Healthcare, Pfizer, and several top universities. The goal is to create reliable tools that generate synthetic data, which will help improve medical research without risking patient privacy. The project has a budget of 22.4 million euros and will run for 60 months.
How Synthetic Data Can Help Healthcare
The main problem in healthcare research is that AI algorithms need a lot of data to work well. However, collecting real patient data can be challenging due to privacy laws. This is where synthetic data comes in. It can mimic real patient data without exposing personal details, making it a safe way to gather large amounts of information. SYNTHIA will focus on generating data for research on cancer, blood diseases, Alzheimer’s, and metabolic conditions.
DNV’s Key Role in the Project
DNV, a company known for its expertise in quality assurance, will play a central role in SYNTHIA. DNV’s job is to make sure that the synthetic data is high-quality, reliable, and safe to use. This involves creating a framework to test and validate the synthetic data. They will also help ensure that the data remains unbiased and trustworthy, which is important for the success of any AI system.
Serena Marshall, the project lead at DNV, said, “We are proud to ensure that the AI systems and the data they use are fit for purpose. Using synthetic data opens up new ways to conduct medical research without compromising privacy.”
Building a Platform for Medical Research
A major part of SYNTHIA is to create a workflow platform for researchers. This platform will include tools to generate synthetic data in many areas, like lab results, clinical notes, images, and genetic information. It will also include a system for checking the privacy, quality, and usefulness of the data. Each dataset will be clearly labeled so that researchers know what it can be used for.
This platform is expected to become a valuable resource for doctors, scientists, and medical professionals. It will provide a secure environment where researchers can access synthetic data tailored to specific health conditions without risking patient privacy.
The Importance of Trust in AI
Building trust in AI-generated data is crucial for SYNTHIA’s success. Marshall emphasized that AI can only be effective if people trust the technology and the data it produces. DNV will work closely with other partners to identify any trust gaps in the data and find ways to fill those gaps. This includes following strict guidelines related to privacy, data quality, and regulations like the Medical Device Regulation and the EU AI Act.
Why SYNTHIA Matters
The SYNTHIA project is important because it promises to speed up medical discoveries while protecting patient privacy. If successful, it could revolutionize healthcare research, leading to better, faster, and more personalized treatments for diseases like cancer and Alzheimer’s. It will also make it easier for scientists to access the information they need without getting caught up in privacy issues.
By creating synthetic datasets, SYNTHIA hopes to provide a way to use advanced AI technology in healthcare research, benefiting both medical professionals and patients.
