Building for a digitized, personalized future

With roots stretching back to the 14th century, the Medical University of Vienna is this year celebrating the 20th anniversary of its independence from the University of Vienna. This ‘old but young’ university is looking to ensure a few more hundred years of pioneering work with a hefty infrastructure investment. “We are connecting our machine learning researchers across more than 14 research groups in areas including imaging, molecular medicine, surgery and pathology, to greatly improve our ability to predict disease course, treatment response, and even detect emerging diseases,” says Georg Langs, professor for machine learning in medical imaging in the university’s Computational Imaging Research lab.

One of MedUni Vienna’s major developments is the Eric Kandel Institute, named after the Vienna-born Nobel Laureate, recognized for discovering the central role synapses play in memory and learning. This precision medicine-focused centre will meld different disciplines, with the aim of developing diagnoses, therapies and preventive measures that are adapted to the specific factors of each person’s condition. One of the institute’s ambitions is to strengthen and broaden the application of precision medicine beyond cancer, where it is currently most advanced, into other areas including neurological and cardiovascular diseases.

With access to clinics in the University Hospital Vienna, one of Europe’s largest hospitals, scientists at the Eric Kandel Institute will benefit from a vast pool of patient data and expertise, both clinical and preclinical.

The heterogeneity of cancer

Precision medicine focuses on the specific characteristics of each individual’s disease, and is already significantly prolonging the lifespan of patients with cancer, says Maria Sibilia, professor for cellular and molecular tumorbiology. Sibilia explains that the value of precision medicine in cancer is in large part due to the heterogeneity of tumours, even among cancers of the same general type. This is becoming ever more apparent as cancer cell genomes are mapped in greater detail. “It is vital to look in detail into the tumour, to be able to precisely target the treatment for each patient,” she says.

Sibilia’s group is focusing on the role of the epidermal growth factor receptor (EGFR) protein, which is pivotal to a molecular signalling pathway that governs both normal cell growth and the aberrant growth of cancer cells. Targeting excessive EGFR signalling is an emerging treatment strategy in cancer, and the MedUni Vienna team want to find out which patients will respond to specific treatments and which might not. They have already found that the receptor plays a different role in different tumours. “It’s really context dependent,” Sibilia explains.

AI is a force in health care

The drive towards precision medicine is assisted by the ever-accelerating developments in artificial intelligence (AI) and machine learning. Langs explains that, at MedUni Vienna, a unique constellation of scientific excellence in medicine, biology and machine learning coincide to make this happen. “We offer an environment where an extremely large, comprehensive and diverse clinical population meets innovative trials, laying the groundwork for novel treatments,” he says. “This fosters cutting-edge research at the forefront of machine learning and precision medicine.”

Christoph Bock, professor of medical informatics in MedUni Vienna’s Institute of Artificial Intelligence, is equally excited by the prospects “AI and machine learning enables things we could never have thought of before.” He explains that work at the university is already developing methods in which researchers, AI systems and medical doctors combine and enhance each other’s strengths. “One really cool example is a laser-based system that allows our neurosurgeons to take rapid digital histological images during surgery,” he notes. “Assisted by AI, this helps determine the precise margin and infiltration of the tumour, leading to better surgical decision making.” He also highlights work on melanoma detection, where computer algorithms and dermatologists combine to outperform either alone, in deciding what is skin cancer.

Bock’s own work focuses on the immune system and its relationship to cancer. His research group is using machine learning to unravel the complexities of immunity and cancer from single-cell data, while also looking at possibilities for new therapies. “If we can learn how cells control their behaviour,” he says, “we can programme them for new biological functions to treat cancer.”

Diversifying into neurodiversity

Ethical animal research could unlock next-generation cardiac care

Victoria Kartysh, a PhD student in Bock’s research group, is excited by the opportunity MedUni Vienna provides for her early steps in expanding precision medicine to address neurodevelopmental disorders. She is creating and characterizing models for hundreds of genetic disorders in parallel, by knocking out their causal genes in stem cell-derived human neurons. This draws connections between autism spectrum disorders, epilepsy, intellectual disabilities and schizophrenia.

“Do the impairments in these different disorders converge on shared pathways, and can such pathways eventually be targeted therapeutically with precision medicine approaches?” Kartysh asks, explaining the ultimate goal of her research.She expects that unraveling the shared and specific regulatory biology underlying diverse neurodevelopmental disorders will not only improve diagnostics but also provides a sound biological basis for the development of targeted therapies for this important group of diseases.

Reflecting on her experiences interacting with colleagues, Kartysh emphasizes the benefits that can flow from the interdisciplinary contacts that the Eric Kandel Institute will foster. “The best research advice I have ever been given came from people outside my area of expertise,” she says, adding, “being part of an inherently interdisciplinary working environment is vital for the progression of science. Presenting your work or simply talking to researchers with diverse backgrounds can provide insights and perspectives that may have never occurred to you.”

In that regard, Langs concurs: “The old days of technical research groups having occasional collaboration meetings with medical application experts are over. The way forward is for everything and everybody to come together from the get-go.”