Interview | Prof. Dr. Petra Ritter, Head of TEF-Health and Dr. Dirk Schlesinger, Head of TÜV AI Lab

On #ai_berlin you can read the complete interview.

Technological advances in AI and robotics have been unprecedented and have captured the imagination of companies, start-ups and researchers alike, with no signs of slowing down. Healthcare is no exception, but new medical devices and procedures must be proven safe and useful before they can be used on patients. And while the European Union has high quality requirements, researchers and entrepreneurs are faced with insufficient testing infrastructure to develop standards, test innovations and certify new products.

The new EU-funded project “Testing and Experimentation Facility for Health AI and Robotics” (TEF-Health), with a total budget of around €60 million, aims to facilitate and accelerate the validation and certification of AI and robotics in medical devices. In conversation with project lead Prof. Dr. Petra Ritter, Director of the Berlin Institute of Health (BIH) and the Brain Simulation Section at the Department of Neurology with Experimental Neurology at Charité and project partner Dr. Dirk Schlesinger Head of the TÜV AI Labwe learned more about their innovative approach, the importance of data accessibility and being at the heart of Berlin's AI landscape.

We are so happy to have you here today to talk about this ambitious project. Could you briefly explain the project, the consortium and what the TEF-Health is all about?

Prof. Dr. Petra Ritter: Thank you very much for having us. The new project is called: “Testing and Experimentation facility Health AI and Robotics” (TEF). It's a big consortium with 51 partners, 9 participating countries and several European institutions. The goal of the project is both to bring innovations in the field of AI and robotics to market and to support our future customers, that are startups and SMEs, in bringing their innovations to market.
 

Dr. Dirk Schlesinger: If I had to summarize the whole project, it would be about three things: First, it's about data, because without data there is no AI, and medical data is sensitive, at the same time rare and needs to be shared. How can you resolve this contradiction? Second, it's about infrastructure, we're talking about learning systems; so we need an infrastructure of supercomputers, labs, and basically places where use cases can be executed. And third, it's about certification. It's about the trust that we need to create as well as the process of how we can bring this innovation to the market. And we need to do it quickly, without consuming too many resources. That's the goal of the project.

Can you explain the idea behind the project and how you plan to proceed?

PR: TEF-Health is organized into nine nodes-each country forms its own node. Based on use cases, we work with startups and SMEs to guide and support the process of certification and validation of applications.

DS: That's a very important point, because with this project we want to pave the way for what we call - for lack of a better term- "agile certification". In today's process, you build something, it's ready, then someone comes and audits it, then it gets certified, and overall it takes forever. We can't do that anymore in AI and especially in medical innovation, it has to be much faster. So we want to develop a process that can be parallelized. Now it gets complex, because there is the research, the company that makes medical devices, the auditor, and finally the certifier, who has to be an independent third party. That's why we need the ecosystem in TEF Health. We need to bring all these players together in one place and then make sure that they have the use cases that Petra was talking about, because that's what process development does practically. This is not an exercise on paper.
 

What is the AI component of the data and the technology behind it?

PR: The brain contains very complex data that provide information about the processes taking place. Comprehensive individual information is needed to develop health applications for the brain that are useful for patients. It is not expedient to anonymize the data of the patients, as this would result in the loss of important individual information. You can't take the complexity or the biometric information - which is as revealing as a fingerprint - out of the data, because then they would basically be useless for most questions. So we need ways to integrate the personal data in a privacy-compliant way to create digital twins of the brain and enable, for example, mechanistic simulations that can be usefully combined with machine learning and artificial intelligence.
 

DS: If I may go into "geek land" for a moment: We're going to work on "federated learning", which means that it's not the data that moves from hospital to hospital, but the model, so we have more data to train the AI. We are talking about homomorphic encryption to ensure privacy of data. There are many different approaches that help ensure that where we think we are at a disadvantage to China and the U.S., we can remedy that because we have the technology to be able to safely and securely provide data for AI training.
 

Why is this project in Berlin and how are you managing it?

DS: There are several reasons for that. First of all, why Berlin? We have the largest ecosystem of AI companies here in this city. Only if we tackle the problems together can we come up with a solution that really helps the patient. Secondly, Petra is based in Berlin and leads the project on a European level. She basically directs the project.

PR: Charité is one of the largest university hospitals in Europe, and as Dirk said, we have a very vibrant research environment. There are many developments in artificial intelligence, both in academia and in industry. This combination of leading medical research and a team to support it, together with this environment and the ecosystem that is being created in Berlin, we are very well equipped to coordinate this major initiative.

DS: It's all about talent, and there is talent here in Berlin. To be honest, it's also about funding, and the Berlin Senate has been kind enough to co-fund the project, and Petra has taken on the responsibility of leading the project from the beginning. So it's a very natural place for everything to come together.                      

PR: Indeed, we have been very well supported. It is very important to note that 50% of the funding comes from the Member States and in our case the Berlin Senate is very helpful in providing co-funding in addition to the Berlin Institute of Health (BIH), which is also supporting the initiative, and we have other supporters like Berlin Partner for example, which is also a very relevant contributor. We also work with institutions like the Physikalisch-Technische Bundesanstalt (PTB) – Germany’s national metrology authority and very important other stakeholders.

Thank you both very much for your insights and all the best for the future of the TEF-Health.

On #ai_berlin you can read the complete interview.

*This interview was conducted by Amira Gutmann-Trieb, Cluster Manager at ICT, Media and Creative Industries at Berlin Partner.

Berlin Partner für Wirtschaft und Technologie GmbH and its health industry and ICT cluster managements supported the project by conducting a stakeholder dialog and workshop with about 50 AI stakeholders from Berlin, exploring TEF funding via the EU Commission, federal ministries and the Berlin Senate, establishing contacts and recruiting additional partners for the consortium, and soliciting letters of interest from companies as potential users of TEF services.