Medical research requires enormous amounts of data to achieve the breakthroughs that make a difference. The more the better – high computing capacities and large amounts of data can aid the development of new diagnoses and treatment methods. The LOOP Zurich is a pioneer in this area, as the center’s annual event showcased.

For big data, more is more, said Prof. Beatrice Beck Schimmer, Director of University Medicine Zurich, in her opening speech.

Data is generated within the healthcare system every day: for example results of blood tests, tissue sample analyses and ultrasound or MRI scans. Such data are used to make a diagnosis and are subsequently archived. But what if computer systems could, with the help of artificial intelligence, autonomously learn from the data collected from patients and even develop new diagnoses and treatments? The evaluation of large amounts of medical data is a major aspect of healthcare research. Where do we stand today – and what are the prospects? These were the questions on the agenda at The LOOP Zurich’s annual event at UZH last week. The LOOP Zurich is a translational research center specializing in precision medicine.

Since 2020, scientists at The LOOP Zurich have been conducting cutting-edge research in precision and data-driven medicine. Researchers from the University of Zurich, ETH Zurich and the four university hospitals conduct joint research at the center – thanks in part to the financial support of foundations. “Research is expensive – but gives society a big return on investment,” said Beatrice Beck Schimmer, Vice President Medicine at UZH, in her opening speech.

One important project that scientists at The LOOP are currently working on is the development of the Biomedical Informatics Platform (BMIP), which provides data for research projects in accordance with the FAIR principle. “FAIR” stands for Findable, Accessible, Interoperable and Reusable. The LOOP Zurich aims to have the BMIP ready to exchange research and health data by 2025. The project, commissioned by University Medicine Zurich, is funded by the Government Council of the Canton of Zurich.

Scientists wishing to access collected health data via the platform for their studies will also receive support to manage the data and to meet data protection and ethical requirements. The entire process from making a request for data to receiving and analyzing the data could thus be completed within a few weeks, said Gunnar Rätsch, professor of biomedical informatics at ETH Zurich.

Christian Wolfrum, ETH Vice President Research, was keen to stress the benefits the platform will yield for patients in the long run. In the future, data from other hospitals and from the field of public health, such as health-tracking data, should also be integrated into the BMIP, added Wolfrum.

Gunnar Rätsch, professor of biomedical informatics at ETH Zurich, describes the path from the research proposal to analysing the data.

Closing the loop from research to patients

Markus Rudin, professor emeritus of molecular imaging and functional pharmacology, emphasized the translation of research findings to clinical application characteristic of The LOOP Zurich projects. “At The LOOP Zurich, we insist that research findings must be fed back into patient care,” he said, introducing two short video sequences presenting The LOOP Zurich projects. INTeRCePT researches leukemia and lymphoma in children and adults. StimuLOOP, meanwhile, aims to treat walking difficulties in Parkinson’s or stroke patients, thus improving their quality of life. Both projects enable patients to receive targeted, gentle and successful treatments, thanks to the precision-medicine approach. 

Markus Rudin (left), professor emeritus of molecular imaging and functional pharmacology and Founding Director of The LOOP Zurich and Giatgen Spinas (right), emeritus professor of endocrinology/diabetology and pathophysiology and Co-Director of The LOOP Zurich.

Supervised and unsupervised machine learning

Computer systems are already capable of independently analyzing health data, learning from them and even using them to establish treatment recommendations. Fabian Theis, professor of mathematical modeling of biological systems at the Technical University of Munich and director of the Institute of Computational Biology at Helmholtz Munich, who was a guest speaker at the event, reported on how artificial intelligence is currently used in practice and the opportunities the use of AI represents for patients.

Artificial intelligence refers to the ability of computer programs to learn. They can do this in two ways, says Theis. The first is supervised learning: researchers show the computer system a large number of similar things and tell it what is right or wrong, healthy or sick, and so on, depending on the question asked. The idea behind this method is that with sufficient input, the algorithm can eventually make the distinction by itself. This can save medical researchers a huge amount of time. But there is also a second way to use artificial intelligence: with this second approach, the computer is given minimal assistance and should be capable of learning without supervision. Mathematician Fabian Theis uses the second method for single cell analysis, for example: the computer receives data about individual cells and their metabolism, and looks for patterns. In this way, new connections can be uncovered.

Challenge of coordinating cantonal data protection laws

The event was rounded off with a panel of experts who discussed the importance of data for the future of medical research from various perspectives. UZH professor of neuro-intensive medicine and chief of service of the neuro-intensive care unit at USZ, Emanuela Keller, described how artificial intelligence in intensive care medicine can provide assistance in making decisions about patients’ treatment, but can also lead to potential conflicts if the AI recommendations do not match the doctors’ empirical knowledge. Gunnar Rätsch and Fabian Theis, along with Michael Krauthammer, professor of medical informatics at UZH, explained how data could be used for research purposes through modern processing methods, and also addressed the data-protection issues that need to be taken into account. Finally, UZH law scholar and medic Kerstin Vokinger spoke about the legal data-protection challenges we will face in the future, particularly in Switzerland with its federalist legal system in which laws differ from canton to canton.

Examined the topic of medical research and data protection from different perspectives: Fabian Theis, Kerstin Vokinger, Michael Krauthammer, Gunnar Rätsch, Emanuela Keller and Markus Rudin (from left to right)

Jens Selige, Geschäftsführer von The LOOP Zurich, stellte am Jahresanlass zwei Siegerprojekte von jungen Jens Selige, general manager of The LOOP Zurich, presented the project prizes, awarded each year at the annual event. Young researchers are able to put their own projects forward for the awards, and if successful win generous financial support for their platforms.

Precise diagnoses thanks to digital image processing

Sebastiano Caprara presented the first winning project: the Biomedical Informatics Imaging Platform (BMI2), run by a consortium of hospitals. Caprara works at Balgrist University Hospital and currently heads the Digital Medicine Unit there. The BMI2 project collects image data, for example from MRIs, and analyzes it using a process called segmentation, a branch of digital image processing and computer vision. “By analyzing the results, we can get more precise diagnoses, for example in the case of damage to individual vertebrae,” says Caprara.

The second winning project, POLAR, was presented by Marco Bühler, a pathologist at the University Hospital Zurich. Researchers working in the consortium plan to gather data from patients with lymphoma. This includes anamnesis, data from imaging, protein analysis and pathology, and genetic information. All these data, currently still recorded in different databases, will be fed into one single database. “We want to compile the world’s largest data set on lymphoma with the aim of using the data to benefit patients in the clinic and contributing to the search for a cure,” said Bühler.

Text: Marita Fuchs
Photos: Frank Brüderli

The LOOP Zurich is a pioneer in data analysis, as the center’s annual event showcased. The aim is to make research available to patients quickly.

Linked Research Projects

Many patients agree to donate their health data to research. Mitchell Levesque, Professor of Experimental Immunodermatology at the University of Zurich, explains how this valuable data is structured, secured and stored. He also argues that access to data should be standardized throughout Switzerland, as this is the only way that Swiss research will be able to keep pace with that of other countries.

Mitch Levesque is a researcher and data specialist. “Collecting health data from patients and – thanks to increasing IT capacities – storing it more quickly and cost-effectively is crucial to medical research in Switzerland,” he says. Levesque knows what he is talking about. As Professor of Experimental Immunodermatology at the University of Zurich, he leads clinical trials at the Department of Dermatology and works intensively on the treatment of skin cancer. In 2014, he began setting up a central tissue biobank. It now contains around 10,000 tissue samples from over 5,000 patients who have consented to their data being made available for research in anonymized and encrypted form. The biobank is used by researchers involved in translational cancer research projects being carried out as part of the University Research Priority Programs (URPP) and is part of SKINTEGRITY.CH, a Swiss-wide initiative on skin research.

“Tumor research is impossible without tissue banks,” adds Levesque, who is also a member of the Tumor Profiler Project (link) team, which analyzes patient data in unprecedented detail. The researchers have already had some initial success: the study results have been fed back into everyday clinical practice; in some patients, the cancer has been prevented from progressing further.

Mitch Levesque, Professor of Experimental Immunodermatology at the University of Zurich

However, donors suffering from an illness are not always able to benefit directly from research results. “It can take years before results are available,” Levesque explains. Donors are aware of this and have other reasons for donating their data: many want to aid the development of new treatments, drugs and therapies. Others are willing to donate their data out of a sense of solidarity with others who are dealing with illness. Their own family history can also play a role, as research using donor data enables the identification of disease-causing risk factors in future generations. For others, access to clinical trials is of direct personal interest. They gain access to new, as yet unapproved drugs or therapies, particularly in advanced clinical trials.

If patients agree to donate their data, the results of laboratory analyses and physical examinations such as blood pressure, X-rays, photos of skin changes, age or gender are stored. Biological samples such as blood, urine and tissue are also stored. 

The use of patient data and samples for research purposes – known as secondary use – is regulated by the Swiss Human Research Act (Humanforschungsgesetz – HFG). By issuing a declaration of consent, also known as “general consent”, the donors consent to existing and future data and samples being made available. In encrypted or anonymized form, these can also be used by other institutions in Switzerland and abroad for research projects. “Tissue samples are released according to a standardized process in which scientific, legal and ethical aspects are taken into account,” says Levesque. “No conclusions about the donor can be drawn.” 

But what exactly happens to the samples? How are they properly stored and preserved? The biobank at University Hospital Zurich contains, for example, tumor biopsies fixed in formalin or frozen human material that is suitable for molecular analyses. A number of tumor tissue microarrays – for DNA and RNA analyses – are also available. On the DNA microarray, all the genes of the organism that is being analyzed are arranged on a glass plate, the “gene chip”, as single-stranded DNA. 

“The sensitive material, such as that from biopsies, is frozen,” explains the researcher. It is important to preserve cells so that they remain viable for years to come. The techniques and tools required to freeze cells properly are challenging. For example, researchers must prevent intracellular ice crystals and cell stress in order to preserve the valuable material along with the important data it contains for further research. 

Standardizing data exchange and organizing it at a nationwide level

The methods used to analyze and process tissue samples and store them in standardized data structures must be consistent, as this is the only way that data can be compared. “Extensive data collection opens up new possibilities for treatment and therapy, but overall, the data exchange necessary for research is lacking in Switzerland,” says Levesque. There is an urgent need for agreement on consistent data storage and structuring methods, as this is the only way to ensure that sufficient data is available for research. 

“Unfortunately, every hospital today has its own IT system. The patient data is therefore not always compatible with other systems and cannot easily be shared by the hospitals or used for research projects. There is no nationwide digital infrastructure,” says Levesque, looking to other countries, some of which are making faster progress in the area of data exchange. 

Levesque praises the “Biomedical Informatics Platform” launched by Academic Medicine Zurich, stating that it is a good step in the right direction. In the years to come, this will allow for the standardized management of research data in Zurich. The four participating university hospitals will send the anonymized data that they have collected for each research project to the new platform. There it will be collated, stored and standardized. 

Levesque is also involved in the Swiss Personalized Health Network (SPHN) initiative. This initiative aims to secure research-relevant molecular and clinical health data and enable the exchange of data required for research. This would enable Switzerland to make progress in the field of data-driven personalized health research at both a national and international level. However, the data specialist warns that Swiss politicians must be prepared to provide cross-cantonal investment, otherwise the country will be left behind. 

Health data:
This is data that relates to a person’s health condition. It includes information about health (diseases, symptoms, therapies) and the results of lab tests, but also details of the person’s lifestyle (diet, smoking, etc.). 

DNA is the molecule that carries genetic information in cells and is passed on to subsequent generations. It is made up of two opposing strands arranged in a double helix structure.

RNA is also a carrier of genetic information, but it plays a key role in protein synthesis and other cellular functions. Unlike DNA, RNA usually consists of a single strand.

Translational research aims to quickly and efficiently translate laboratory findings into clinical applications that benefit patients.

Biobanks are collections of biological samples and related data in a structured form. Biobanks for medical research typically contain tissue samples, blood or other bodily fluids, as well as cells or DNA samples of human origin.

Immunodermatology is a specialism that examines the interactions between the immune system and the skin. The focus here is particularly the immunological aspects of skin diseases.

Many patients agree to donate their health data to research. In Zurich, this valuable data is structured, secured and stored.

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Newsletter abonnieren

New developments in medicine are coming thick and fast. Technological advances are increasingly making it possible to understand diseases and the processes taking place in the human body down to the level of individual genes and cells. This brings definite benefits for patients. The earlier an accurate diagnosis can be made and the more precisely a disease can be treated, the greater the prospects of a cure or an improvement in the patient’s quality of life. Nowadays, treatments can be tailored to individual patients more and more effectively. This is what is known as precision medicine and the pioneering field in this area is oncology. We now know that every tumor is unique. If we can analyze the genome of tumor cells, for example, we will have a better chance of making a targeted attack on their weak points. 

Gene analyses of this kind and other modern diagnostic methods produce large volumes of data. Artificial intelligence makes it easier to evaluate these data and, for instance, to detect patterns that indicate why diseases occur. Therefore, the hope is that it will be possible in the future to prevent, diagnose and treat many diseases much more effectively than in the past. 

The growing volume of data in the field of medicine must be used in order to achieve this. The central elements of this process are the interdisciplinary cooperation between researchers at the interfaces to medicine – for example from the fields of informatics, biomedicine and law – and the involvement of the patients, because we can only shape the medicine of the future by working together as a society. To gain a better understanding of the accompanying opportunities, we have shone a spotlight on different aspects of this subject. They range from a common platform for data sharing to groundbreaking new technologies and questions of ethics and data protection.

Data in Precision Medicine