ABSTRACT
The idea of fitting mathematical models to a data set can be thought of as putting a calculated line through the observed data points. The mathematical model used to explain analytical standard curves is often the equation for a straight line. The principal objective, while mathematically modeling pharmacokinetic data, is to find parameter values that will reduce the differences between the observed data and the calculated line. The relationship between drug effect and drug concentration is an example of another model that is not easily converted into a straight line. The basis of mathematical modeling is to describe a series of observations using an equation. In most cases this equation includes a number of unknown parameters. The objective of the modeling process is to adjust these parameters to produce the optimal fit to the data.
