Pharmacogenetics And Individual Variability: Simulation Using Agent-Based Programming
There is a critical need for new innovative approaches to understanding and modeling interindividual variability and how it impacts development of new therapeutic strategies, e.g., new drugs, as well as the utilization of existing therapeutic strategies. Individual patient variability, such as cardiovascular status, pharmacogenetics, etc. are known to contribute to pharmacodynamic variability. Such variability is difficult to capture using traditional modeling strategies. We are successfully using a novel approach that uses an agent-based programming platform (e.g., SWARM.) The approach can provide an in silico patient population that responds appropriately to drugs based on individual patient attributes. While current approaches in the field rely heavily on complex, often stiff statistical models that are drug specific, our in silico approach offers the ability to model random biological fluctuations inherent in human populations along with a program which may be easily modified to test an array of therapeutic products. The long-term and potential groundbreaking benefits of such an undertaking include targeting appropriate populations for drug safety and efficacy trials, and having a tool that can be used to optimize drug regimens for specific patients.
Key personnel: Amina A. Qutub
Collaborators: Alex Lancaster
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...