Bridging the Gap to Patients
This week, the University of Zurich held a symposium to mark the newly established Department of Quantitative Biomedicine. The research institute strengthens UZH’s standing in the field of precision medicine. We met with its director Bernd Bodenmiller to discuss how the department’s methods can be used to benefit patients.
Bernd Bodenmiller, you head up the Department of Quantitative Biomedicine and this week celebrated the founding of the new department with a scientific symposium. What are you thinking right now?
Bernd Bodenmiller: I’m very happy that we were able to finally celebrate founding the new department in public together with our colleagues, the team and everyone who was involved. The symposium completes a founding process that lasted several years and marks the beginning of a new phase in which we can start putting our vision into practice.
How did the new department come into being?
It’s a long story, which began in 2016. The Swiss Personalised Health Network initiative (SPHN) got the ball rolling with the aim of promoting personalized medicine and healthcare across Switzerland. Together with then Vice President Research Christoph Hock, we asked ourselves what the University could contribute to this network, and one of the answers was the Department of Quantitative Biomedicine.
Could you explain what quantitative biomedicine is?
Quantitative biomedicine is a broad field. For example, we want to use quantitative analysis and algorithms to better understand the causes of diseases, and this will enable us to develop precision medicine treatments. Some of our research groups’ work involves large amounts of clinical and patient data, and we then use computer-assisted methods to try to improve treatments directly.
So quantitative biomedicine begins and ends with the patient?
You could say so, yes. Our research starts either with a tissue sample from patients or their data, or both. The findings we obtain in this way benefit the patients in the medium term, or can directly improve treatment quality.
In the TumorProfiler project, for example, my group works with tissue samples taken from tumor patients. The imaging methods we use give us a detailed picture of the tissue right down to the level of individual cells. We then analyze these huge amounts of data using computer programs and draw conclusions for treating patients. Our findings are then also presented to the clinic’s tumor board.
What exactly does “quantitative” mean, for example when it comes to cancer tissue?
The “quantitative” refers to the fact that we very carefully analyze the biological characteristics that interest us. This enables us to base our analyses on computational methods. In the case of cancer tissue, we analyze the type of tumor cell, the immune cells in the tumor, the way the cells interact, which processes are deregulated, and much more. Another good example here is the research of group leader Björn Menze, professor of biomedical image analysis. He uses machine learning to automatically map and analyze tumor images. I always like to compare this to an iceberg, where at the surface we can see a tumor, but beneath this are countless different components. These data are so complex that we can only analyze them with the help of computational methods.
Can this be implemented in the clinic? In the end, it’s only about deciding for or against a drug?
That’s a key issue. How can huge amounts of data be analyzed and broken down into a short list of recommendations that medical specialists can implement? It’s a great challenge and also one of our tasks. This is one of the fields of the research group of Michael Krauthammer, professor of medical informatics. At the same time, in terms of quantitative biomedicine it’s too short-sighted to focus only on direct clinical application. Our goal is also to identify new patient groups and investigate their disease mechanisms. Findings in this area can then also be used in the clinic in the medium term. The research group of Magdalini Polymenidou, professor of biomedicine, is concerned with this basic research through their work on neurodegenerative diseases.
Is the new department more focused on carrying out applied research or basic research?
Our focus is on bridging the gap between basic biomedical research and clinical application. The quantitative methods used to map and analyze large amounts of data are the bridge, so to speak. Two of our research group leaders, Michael Krauthammer and Björn Menze, don’t have their offices at the department on Irchel Campus, but at the UniversityHospital to promote this cooperation.
The department has five research groups, from evolutionary biology to medical informatics. What binds them together?
We each benefit from the others’ research and in this way enhance our own research and teaching. That’s the main strength of our department. We’re united by our mission: Using the complete cycle of quantitative biomedicine including patient samples, quantitative and computational analyses to personalize and improve treatment options for patients. These are the areas in which we want to achieve meaningful progress.
But the disciplines have quite a broad view?
We decided right at the beginning that we wouldn’t focus on any one biomedical topic, but instead take a broad approach. We now have five groups in the areas of neurodegeneration, microbiology, oncology, medical informatics and machine learning, and we will soon add a sixth group focusing on immunology. This topical breadth benefits research and teaching activities across the entire department. Rolf Kümmerli, professor of evolutionary microbiology, whose research concerns bacterial networks, has given us interesting insights in the area of cooperation and competition. His microbiology concepts can also be applied to other diseases and open up new treatment approaches.
What motivated you to become the department director?
I find it incredibly exciting to work at the intersection between biomedicine, biotechnology and computational methods to develop personalized treatments for patients. I really enjoy helping to set up and support organizations that carry out research and teaching activities in this area. Thanks to my own research, I have lots of experience in the areas that matter when it comes to quantitative biomedicine. This enables me to bring together the multidisciplinary lines of research in quantitative biomedicine and realize our vision of bridging the gap between basic research and clinical practice.
The founding symposium featured many of your peers from different universities in Switzerland and abroad. Is quantitative medicine experiencing a boom?
Yes, the field is indeed on the up and up. This also has to do with the increasing number of new technologies in the area of quantitative analysis of biological systems and the ever-improving algorithms that help us understand the data. Numerous initiatives, for example in the US, Great Britain or Germany, are behind this development. The development is driven by the expected benefits for patients.
Quantitative methods aren’t only popular in biomedicine, are they?
The whole field of biology is currently taking strides toward the data sciences. More and more biological research areas are shifting to computational methods. That’s why it makes sense that all biology students at UZH should learn how to program.
What is the new department’s significance for UZH?
The department is a logical response to the rapid developments we just mentioned. It enables us to be at the forefront in this field. As a joint department of the Faculty of Medicine and the Faculty of Science, we’re in an ideal position to bridge the gap to clinical practice and to the patients. Together with the Digital Society Initiative, we’re also stepping up education in the field of computational methods. There’s a huge demand for people with these skills.