RG Modelling of Immune Processes (Graw)

Our research aims at analyzing the immune system and its complex dynamics in the context of infection, inflammation and malignant diseases.

By combining experimental and clinical data with methods from mathematical modelling, systems biology and data analysis, we aim at getting a mechanistic and quantitative understanding of how immune responses are generated, how immune cells interact and work, and which processes and factors govern these complex dynamics and determine disease progression. We especially aim at developing methods that allow the combination of various biomedical data (e.g. single cell measurements, imaging, serology) to provide an integrated analysis of the processes involved during immune reactions. Thereby, our methods comprise individual cell-based models and computational simulations of tissue structures, as well as methods from machine learning for analyzing complex data sets and model systems.

One aim of our research is to determine how cellular immune responses (T-Cells, B-Cells) are activated, distributed, regulated and maintained, especially in the context of immunotherapy and vaccination. Hereby we aim at addressing questions concerning the interaction of immune stimulating and inhibiting factors, the generation of tissue- and tumor-specific immune responses, as well as to predict the progression of CAR T-cell therapies and the development of graft-versus-host disease (GvHD) after allogenic stem cell transplantation.

In a second line of research we aim at deciphering the complex dynamics of inflammation and immune processes within tissues, as e.g. within tumors or during infection. Hereby, we analyze how local immune responses are generated, how local inflammation influences tissue pathology, and how tissue structures determine the efficacy of immune responses. Our approaches should help to determine the influence of individual cell characteristics, molecular concentrations and pathological changes on disease progression and to identify potential therapeutic approaches.

• Prof. Dr. Frederik Graw (Group Leader)
• Pascal Lukas (PhD student)
• Lennart Wicker (PhD student)
• Julia Hafenbrak (PhD student)
• Szilard Varga (PhD student)
• Lorenz Glück (MSc student, Physics)
• Anna-Lena Rösch (MSc student, Integrated Life Sciences)

Alumni:

• Dr. Laeschkir Würthner (PostDoc), Aastha Thapaliya (MSc student), Marie-Luise Plescher (PhD student)

We always welcome applications from skilled and motivated BSc, MSc and MD students of different disciplines interested in doing a project or thesis in the field of Theoretical and Computational Immunology. Applications and topics address immune and infectious disease dynamics, fundamental questions concerning immune processes within cancer, immunotherapy and vaccine design.

Collaborations – intern

• Prof. Dr. med. Fabian Müller (Dept. of Medicine 5 – Hematology & Oncology, Erlangen)
• PD. Dr. Simon Völkl (Dept. of Medicine 5 – Hematology & Oncology, Erlangen)
• Dr. Gloria Lutzny-Geier (Dept. of Medicine 5 – Hematology & Oncology, Erlangen)
• Prof. Dr. Kilian Schober (Institute for Microbiology, Erlangen)
• Prof. Dr. Dr. Sebastian Zundler (Dept. of Medicine 1 – Gastroenterology, Erlangen)

Collaborations – extern

• Prof. Dr. Annette Oxenius (Institute of Microbiology, ETH Zurich)
• Prof. Dr. Oliver Fackler (Institute of Virology, Heidelberg Univ.)
• Prof. Dr. Wolfgang Kastenmüller (MPRG Systems Immunology, Univ. Würzburg)
• Prof. Dr. Christoph Scheiermann (Dept. of Pathology & Immunology, Univ. Geneva)
• Prof. Dr. Jan Hasenauer (Computational Life Sciences, Univ. Bonn)
• Prof. Dr. Ullrich Koethe (Explainable Machine Learning, Heidelberg Univ.)
• Dr. Jeremie Guedj (Infection Antimicrobials Modeling Evolution, INSERM, Univ. Paris Diderot)
• Dr. Olivier Terrier (Respiratory Coinfections, INSERM, CIRI Lyon)

• German Science Foundation (DFG)
  • DFG/ANR-Project MORIARTY - Modelling of viral respiratory co-infection dynamics in human epithelium
• Federal Ministry of Education and Research (BMBF)
  • EMUNE - Enabling Mechanistic Understanding in Infectious Disease Research using Invertible Neural Networks
• Bavarian Center for Cancer Research (BZKF)
  • CAR T Control - Understanding and Addressing Toxicities of CAR T-Cell Therapy
• Boehringer Ingelheim Foundation (BIS)
  • Revealing T cell turnover and trafficking dynamics by single cell-based mathematical modelling