Other - Mathematical Modeling of Immune System Activity
Adding computer-based system simulation to medical research processes could enhance the progress of some immunological research, potentially reducing the long time and high cost of successful drug development for treating long-term chronic disorders. Expanding the use of system simulation modeling would help advance the analysis of the elegantly complex, feedback-intensive processes that make up the human immune system and its interaction with disease conditions.
The benefits of doing so include the ability to: (1) examine the performance of long-term chronic conditions (such as autoimmune and neurodegenerative disorders and cancers) in high-speed analyses; (2) test rapidly and systematically each of many different possible points of intervention in the system, to identify those with the most leverage in improving a disease condition; (3) test combinations of interventions (treatments and potential cures), because some systemic disorders will likely require combination therapies—some of these could be difficult if not impossible to find with real-time experiments; and (4) test alternative hypotheses of the systems’ workings—having a platform to test explicitly different theories about current unknowns would be a valuable aid to advancing our understanding.
This presentation offfers arguments for expanding system modeling as a weapon in the fight against cancers, autoimmune and neurodegenerative disorders, and more--a productivity-enhancing prelude to clinical research. Examples presented will illustrate simulation models that have been built and used to analyze immune diseases and disorders such as HIV, type 1 diabetes, CTE and others. It is written not by a medically-trained scientist, but rather entirely from a system modeler’s viewpoint.