INTERVIEW of alcohol addiction or something like that, then it might be more difficult to get one of these things. I once tried to take out a life insurance policy. My wife said: “But then you can’t go mountain climbing or anything like that.” In my opinion, first of all, you have to be completely transparent about it, and secondly, you have to set clear legal conditions about how far you can go with the policies. That’s obviously not my area of expertise. But I think that jurispru- dence, and perhaps also medical ethics, will have to deal with this very thoroughly. What fascinates you most about your work? We were just talking about the scientific stuff, but I almost think that the coolest or most beautiful thing is to be able to work in international teams with fantastically smart PhD students from all over the world, very diverse backgrounds, but so highly intelligent and so creative. It’s really fun. First, these methodologies that I have in my lab, but then bringing them together with experimental colleagues. We always want to work on data and thereby learn new things, but also create new results along the way. That’s always exciting, you always have something new to do, and hopefully we won’t be replaced by AI any time soon. In addition to high-ranking awards, you have recently been honored with the Gottfried Wilhelm Leibniz Prize. This prize is somewhat equivalent to the German Nobel Prize. What does this award mean for you and your research? First of all, it’s a recognition of the work we do here in the lab. My staff and I are really proud when we hear something like that. Yes, we were very happy. When we arrived in Berlin together with the whole family and were able to enjoy a really nice celebration, it’s something like that when you take a deep breath. With us, everything often happens very quickly. One paper finished, the next one already in prepara- tion, and the research results are just so exciting. During the COVID pandemic, we were able – and also had – to find answers to so many new issues. That was an exciting thing in the first place. But beyond that, it is a matter of course that this prize enables me to tackle and discuss a new research topic for which I don’t have my own fund- ing. The prize is relatively well endowed… very well endowed, and so I have to think about choosing a highly exciting new field, in which I am not normally so well informed or have not yet had a chance to get to grips with, and so we are trying to do more with generative AI models. Where do you want to go from here? Is there a higher level for you? Well, scientifically speaking, there is always a progression. Scientifically, nothing rests here. Biology, biotechnology, very well sup- ported by BioM, is incredibly fast. There is always a new device, a new machine that can measure something new, and for all these new observations, maybe also chron- ologically arranged, we will maybe some- day finally have a health record in Germany. Models are needed, and all these models should perhaps also be integrated. In other words, the wave of data that is coming our way is not going away. It is getting bigger and bigger, and we want to dig through it, we want to build understandable models that can then be given to the population as interpretable results. These are really difficult issues, and we will never get bored. Since 2020, you have been co-chairing the AI Council of the Bavarian State Government to bundle and network AI expertise in Bavarian science, industry, and society. Where do we stand in terms of the use of AI for medicine in Bavaria and in Germany? First, it has to be said that we in Germany are good in all kinds of areas due to very substantial long-term science funding. A lot has been invested in AI, especially here in Bavaria, through the Bavarian high-tech agenda, and we have always had and built up very strong expertise here in Munich. We are one of the largest centers now for “Health AI”, or, as I always say, “AI in health research”, with about 250 people and 30-35 group leaders here at the Computational Health Department at Helmholtz Munich alone. In addition, we have a whole range of extremely strong colleagues and partners at the TU and LMU. In this respect, there is really bundled expertise here. It’s great to bring together, through this AI Council, all these different individual initiatives and to communicate them in a way that people see themselves reflected externally, so that when we want to bring top people from the U.S. or the whole world to us, for example, we can tell them more clearly and show them in a more focused way what expertise and opportunities are here - not only in science, but naturally in business as well. Health data play a relevant role in your work. Compared to Germany, such data are more readily available in other countries such as the USA, Finland, Great Britain or Israel. Is the situation here in Germany more of a hindrance for your research? Data availability is absolutely a hindrance. A very clear point, yes! If you are working on model organisms or cells, it doesn’t play such a big role at the moment. But as soon as we want to look at patient co-variables or something like that, we are simply not as fast or as digital as in other places. For papers, I can simply collaborate interna- tionally. For my scientific research, we work beyond that. But we don’t advance the sys- tem that much here. In this respect, I am very excited. I’m very happy that the elec- tronic health record will soon be available here as well. Honestly, I personally would love to own my data that the different doctors generate. I don’t remember when I had my last doctor’s visits. Or I would also like to be able to see on my phone what medication my parents have right now, etc. I think that’s where we need to become more digital. If we have something like that, You can listen to the full interview from our BioM podcast series Biotech Talk aus Bayern in German at: www.bio-m.org/Podcast/Interview_Theis 28 BIOTECH IN BAVARIA - REPORT 2022|23