Computational Biomedicine

Menden Lab

The mission of our research group is to develop biostatistical and machine learning frameworks applied to biomedical data, to retrieve insights in the aetiology of complex diseases and identify novel intervention strategies. For this, we explore deep molecular characterised biomedical datasets, environmental factors, and tailor our models depending on disease specific knowledge gained through collaborations, literature and data driven analyses, thus empowering the next generation of drug target identification, drug repositioning and precision medicine.

Computational Cancer Pharmacogenomics

We have strong expertise is in computational method development for cancer pharmacogenomics including the analysis of monotherapy and drug combination high-throughput screens, and lately, CRISPR lethality and drug resistance screens, which is highlighted by our recent ERC Starting Grant. The Menden Lab customises machine learning and biostatistical methods to predict drug sensitivity and synergy, as well as derived genetic biomarkers of these responses. Our work focuses on clinical translatability and interaction with the microenvironment, and thus enables patient stratification based on deep molecular profiles, which is the key pillar of precision.

Translational Computational Pharmacogenomics

The foundation of our endeavour is our strong expertise in Computational Cancer Pharmacogenomics (ERC StG), which we envision to generalise to the Translational Computational Pharmacogenomics. In particular, we expand our research focus to tuberculosis drug resistance (bayresq.net, UNITE4TB), inflammatory skin diseases (IGSSE), neurodegenerative diseases (MUDS) and diabetes (DZD). Common across all projects, we are experts in analysing deep molecular characterisations of patients and disease models to stratify samples into drug responders or phenotypes, which ultimately enables precision medicine. In essence, our research vision is to establish a Translational Computational Pharmacogenomics programme in cancer and beyond, in order to accelerate the delivery of urgently needed targeted therapies.

Other Links:

Dr. Michael Menden
Twitter Profile (@MendenMichael)