Computational Approaches to Disease, Signaling and Drug Targets
The Minor Computational Approaches to Disease, Signaling and Drug Targets (CADSDT) is focused on fundamental scientific research required for discovery of new drug targets and development of new drugs.
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Chronic progressive diseases such as cancer, diabetes, neurological disorders, or cardiovascular disease result from changes at the cellular level that disturb the biology of healthy tissue. Dissection of the primary molecular mechanisms that underlie both the initiation as well as progression of diseases can lead to the identification of novel targets for drug intervention. The regulation of cell biological processes occurs by complex, cell-specific signal transduction cascades both within affected cells and between different cell types in the affected tissue and/or organism. The interactions of drugs with the biological system can also be studied at these different levels.
The goal of this Minor is to provide insight into general signal transduction pathways, how these pathways are altered in disease and upon modulation with pharmacological agents and how fundamental research of these processes can be used for the discovery of new drug targets. Importantly, a large part of the Minor focuses on exploiting computational approaches to achieve these goals (which are practiced by hands-on exercises). For example, it shows how these alterations in signaling can be dissected using modeling of network dynamics as well as bio- and cheminformatics approaches. Furthermore, this Minor shows how insights in the changes in molecular pathways of disease constitute the basis for the identification of biomarkers that can be used for monitoring disease progression in patients. This is important for the development of new drugs aiming at modification of disease progression. In addition, a new course in stem cell biology in drug research provides fundamental and applied aspects in the differentiation of stem cells for drug research. Mechanism-based pharmacokinetic, pharmacodynamic, and disease progression models are presented which, in combination with new biomarkers, constitute a scientific basis to assess the effects of novel drug treatments in clinical trials.