This is the webpage of Thomas Stiehl. I am mathematician and medical doctor. In my research I develop mechanistic mathematical models with applications in the biosciences. My focus is on cancers of the blood forming system, such as acute myeloid leukemias (AML) and myelodysplastic syndromes (MDS). The models help to better understand disease mechanisms and to predict the course of the disease based on clinical data. This is a first step in the adaptation of treatments to disease characteristis of indiviual patients (personalized medicine).
Areas of focus:
Mathematical modeling of stem cell dynamics and disease progression in blood cancers (AML, MDS, MPN), including the role of clonal selection/clonal competition, systemic feedback-mechansims and processes in the stem cell niche.
Model-based risk-stratification and personalized prediction of disease progression in blood cancers.
Mathematical modeling of blood cell formation in health and disease, including reconstitution after bone marrow transplantation (recovery of blood cell counts) and white blood cell formation in sepsis.
Mathematical modeling of stem cell aging including blood-forming stem cells, neural stem cells and mesenchymal stromal cells.
Mathematical modeling of neurogenesis in the adult brain.
Mathematical modeling of stem cell dynamics in plant meristems.
Mathematical modeling provides evidence for niche competition in human AML and serves as a tool to improve risk stratification, Cancer Research 2020. Stiehl et al.
Quiescence Modulates Stem Cell Maintenance and Regenerative Capacity in the Aging Brain, Cell 176, 2019. Kalamakis et al.
Reduced hematopoietic stem cell frequency predicts outcome in acute myeloid leukemia", Haematologica 102, 2017. Wang, Stiehl et al.
Cell division patterns in acute myeloid leukemia stem-like cells determine clinical course: a model to predict patient survival, Cancer Research 75, 2015. Stiehl et al.
Clonal selection and therapy resistance in acute leukemias: Mathematical modelling explains different proliferation patterns at diagnosis and relapse, J. Royal Society Interface 11, 2014. Stiehl et al.