After completing the material in this chapter each student should:-

* understand exponents and logarithms, algebraically and graphically

* be able to use linear (Cartesian) and semi-log graph paper for the representation of data

* be able to draw a 'best-fit' straight line through data on linear and semi-log graph paper

*understand and able to use spreadsheets

* understand differential and integral calculus

* be able to write differential equations given a compartmental modeling scheme as a diagram or description

* be able calculate the area under the plasma concentration versus time curve (AUC) using the linear trapezoidal rule

With linear disposition pharmacokinetic models (distribution, metabolism and excretion first order) it is possible to add concentration from various doses together to get the total drug concentration. Various types of doses can be included at various times.

With linear disposition pharmacokinetic models (distribution, metabolism and excretion first order) it is possible to add concentration from various doses together to get the total drug concentration. Various types of doses can be included at various times.

Given the requirement that Cpmax and Cpmin are close to but below specified values we can calculate a suitable loading dose, maintenance dose and dosing interval.

Given the requirement that Cpmax and Cpmin are close to but below specified values we can calculate a suitable loading dose, maintenance dose and dosing interval.

The parameter values kel and V can be determined from the 'best-fit' line drawn through the data on semi-log graph paper.

Given the requirement that concentrations stay between Cpmax and Cpmin we can calculate a suitable loading dose, maintenance dose and dosing interval.

The absorption parameters, ka and V/F, can be determined from oral data. For good estimates of these parameters the ratio between ka and kel must be greater than 5. Also the absorption and elimination should be first order