About the project

Improved treatments of Acute Myeloid Leukaemias by Personalized Medicine

In the AML_PM project we will develop a novel approach to classify patients by their genetic profile and the status of internal cell signalling associated with the disease to help tailor treatment for the individual patient. In the project we will combine use of mathematical models of signalling pathways with detailed data on gene expression, abundance and forms of proteins in individual cells and patients and relate these to treatment response and prognosis. Model building will proceed in parallel with experimental work on model systems. Machine learning will be utilized to predict disease subtype and to help tailor treatment. The project will initially focus on a small subset of AML, pure erythroleukaemia (PEL), to develop a feasible pipeline to gain insights into disease mechanisms and propose personalised treatment options. This strategy is applied to other AML cases and utilised to optimise therapy for the individual patient. Proof-of-concept validation in patients will be performed when possible.

Inge Jonassen, University of Bergen, Norway



Bjørn Tore Gjertsen, Haukeland University Hospital, Norway

Jan Jacob Schuringa, University of Groningen, The Netherlands

Ursula Klingmüller, German Cancer Research Center (DKFZ), Germany

Jens Timmer, University of Freiburg, Germany

Mels Hoogendoorn, Medical Center Leeuwarden, The Netherlands

Aaron Schimmer, University of Toronto, Canada