A foundation for the control of tumors is presented,
based upon the formulation of a realistic, knowledge-based
mathematical model of the interaction between tumor cells
and the immune system. The parametric control variables
relevant to the latest experimental data, e.g., the sigmoidal
dose-response relationship and Michaelis-Menten dynamics,
are also considered. The model consists of 12
states, each composed of first-order, nonlinear differential
equations based on cellular kinetics and each of which can
be modeled bilinearly.
In recent years a great deal of clinical progress has
been achieved in the use of optimal controls to improve cancer
therapy patient care. For this study, a cancer immunotherapy
problem is investigated in which the aim is to
minimize the tumor burden at the end of the treatment period, while penalizing excessive administration of
interleukin-2 as a limit of toxicity. The optimal solution
developed for this investigation is a mixture of an initially
large dose of interleukin-2, followed by a gradually
decreased dosage and a continuing infusion to maintain the
tumor cell population at its allowable limit.
Sensitivity analysis is applied to an investigation of
the influences of system parameters. It has been found that
the immune system is influenced greatly by several parameters
such as macrophage level, tumor killing rate, tumor
growth rate, and IL-2 level.
The simulation results suggest that parametric control
variables are important in the destruction of tumors and
that the application of exacerbation theory is a good method
of tumor control. / Graduation date: 1991
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/37483 |
| Date | 23 July 1990 |
| Creators | Lee, Kwon Soon |
| Contributors | Mohler, Ronald R. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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