Elucidating Critical Elements Within Pharmacogenetic and Biomolecular Pathways

We are systematically evaluating the applicability of graph theoretic techniques to facilitate utilization of large pharmacological, genetic and physiological system models. The conceptual or computational model (such the above Stochastic Activity Networks) in is first represented as a network graph having nodes and edges with respective weights. Computational graph analysis is then used to bring critical elements into focus by grouping closely related system elements prior to finding and ranking elements or paths between elements that have the greatest influence on the system. When applied to pharmacological and physiological system models, such "critical elements" represent potential drug targets. By modulating the function of these elements or specific interactions between elements, we expect to be able to identify the process or event where intervention is most likely to have the greatest effect on potential outcome functions, such as drug or treatment effectiveness or undesired side effects.

Key personnel: Abraham Anderson.

Collaborators: Richard Ho, Director of Medical Informatics, R.W. Johnson Pharmaceutical Research Institute.

 
 

The premise of the agent paradigm, its related theory and methodologies together with advances in multilevel modeling of complex systems of interactions opened new frontiers for advancing the physical, natural, social, military, and information sciences and engineering...