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7 Cards in this Set

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data analysis approach

fit the data by a proper equation
for a 3 compartment model:
c= a1*e^-b1*t + a2*e^-b2*t + a3...
data analysis: fitting procedure

pharmacokinetic models are nonlinear with respect to optimized parameters, ie:
the dependent variable c cannot be described as the sum of functions of independent variables (time t) multiplied by the optimized parameters
initial estimates can be obtained by the:
methods of risiduals (peeling, feathering)
the best model is selected using statistical criteria that include the quality of the fit:
--x^2, sum of squares of deviations (the smaller the better, but cannot be smaller than the experimental error. does not consider the number of parameters)
--the correlation coefficient r (percentage of explained variance = r^2. the closer to 1 the better)
--the F-test criterion
another criterion: the deviations between the model and the experimental points need to be distributed:
homogeneously

see slide page 1
if several models are of equal quality, the simplest model (containing the smallest number of optimized parameters) is selected. The rule is called:
Occam's Razor
data analysis: summary
- method of residuals used to get initial estimates of the model parameters
- the parameter values are refined using nonlinear regression analysis
- for single dose, number of exponentials = number of compartments if the exponents are sufficiently different.