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Results
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AI-driven Atlas for Spatial Proteomics
We develop a generative AI toolkit for spatial proteomics, capable of virtually staining tissue images for different protein types, harmonizing existing data, and creating a unified atlas of human cancer. This project, funded by the Chan Zuckerberg Initiative, aims to develop a generative AI toolkit
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Genome of Switzerland
We are participating in this collaborative project aimed at better understanding the distribution of genetic variations among Swiss population. This information will help to better identify the genetic causes of diseases and improve personalized medical care. A nationwide initiative designed to gene
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Développement du BioHub de la Skin Science Foundation
L’objectif de l’étude est de poursuivre le développement du BioHub de la Skin Science Foundation afin d’accélérer et de faciliter la standardisation, le partage et la réanalyse des données. Cette initiative vise à faire progresser la science fondée sur les big data et la médecine de nouvelle générat
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Advancing Mesothelioma Treatment with AI-Enabled Precision Oncology
We integrate different types of data to provide a comprehensive view of the tumor microenvironment and better understand the complex ecosystem of tumors. The study focuses on mesothelioma, a rare cancer for which there is currently no effective treatment. In this project, funded by Swiss Cancer Rese
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AI-driven Insights into the Tumor Microenvironment
We leverage spatial omics technologies and develop interpretable AI models to better understand the complex interactions within the tumor microenvironment and enable more precise and personalized cancer therapies. Cancer research has shown that tumors are complex ecosystems where cancer cells intera
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PROMETEX: Metabolically-instructed personalized therapy selection for prostate cancer
We combine AI with patient-derived cancer cell models (organoids) to analyze tumor cell metabolism at the single-cell level and develop personalized treatments for prostate cancer. Prostate cancer is a complex disease for which treatments are often not effective due to the cancer’s high variability—
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Sustainable COVID-19 Vaccination for Long-term Immunity and Effectiveness
We take part in the European SOLVE project, which aims to develop advanced vaccine technologies for stronger and longer-lasting protection against COVID-19. Within this project, our team builds and maintains a system for managing and analyzing high-dimensional data generated during vaccine trials. W
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Creating a spatially-resolved omics reference database in oncology
We are part of the MOSAIC consortium, which aims to build the largest reference dataset in spatial omics for oncology. This dataset will help uncover treatment resistance mechanisms and improve patient stratification, ultimately paving the way for the discovery and development of personalized therap
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Predictive biomarkers of response to immune checkpoint inhibitors
As part of the European IMMUcan project (Integrated iMMUnoprofiling of large adaptive CANcer patient cohorts), we are working on identifying new predictive biomarkers of response to immune checkpoint inhibitors. IMMUcan is a European consortium which focuses on uncovering the role of the tumor micro
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MED.USE : Medical large language model for reducing resource overuse in the emergency department
We develop a decision-support system based on a medical language model, capable of processing commonly available information and providing recommendations to emergency department clinicians, with the goal of reducing low-value care. This project, funded by the Swiss National Science Foundation, aims