Executable network models to identify new treatment combinations for leukaemia

Established: June 4, 2012

Chronic Myeloid Leukemia (CML) represents a paradigm for the wider cancer field. Despite the fact that tyrosine kinase inhibitors have established targeted molecular therapy in CML, patients often face the risk of developing drug resistance, caused by mutations and/or activation of alternative cellular pathways. To optimize drug development, one needs to systematically test all possible combinations of drug targets within the genetic network that regulates the disease. We previously built a CML network-model using BMA, encapsulating experimental data collected from some hundreds publications. We used the model for in silico experimentation probing dynamic interactions between multiple pathways and cellular outcomes and suggested new combinatorial therapeutic targets. Currently, we are in the process of building similar network models for Acute Myeloid Leukaemia (AML).

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