R. Gomeni et al., POPULATION-KINETICS AND CONDITIONAL ASSESSMENT OF THE OPTIMAL DOSAGE REGIMEN USING THE P-PHARM SOFTWARE PACKAGE, Anticancer research, 14(6A), 1994, pp. 2321-2326
The adjustment of individual dosage regimen is an adaptive control pro
cess based upon an individual response to a pharmacokinetic model. To
attain this objective, if is very helpful to know the characteristics
of the population to which the subject belongs, in terms of mean param
eters and interindividual variability. Usually the available informati
on consists of incomplete and sparse data. For this reason it is essen
tial to employ a computational methodology based on non-linear mixed-e
ffect procedures in order to obtain a population parameter estimate. A
Bayesian methodology can then be applied from the population paramete
rs to the specific data for the individual requiring a dosage adjustme
nt (such data includes drug concentration(s) of the active drug, demog
raphic data, etc). The result of the Bayesian calculation supplies the
required individual pharmacokinetic parameters. An optimal dosage reg
imen can be defined on the basis of therapeutical criteria (concentrat
ion ranges) as well as practical constraints such as: the size of avai
lable unitary drug dosages, feasible drug intake times, penalties asso
ciated with expected concentrations falling outside the therapeutic co
ncentration ranges. In this paper we present the methodology and resul
ts obtained using the P-Pharm software tool. P-Pharm implements a non-
linear mixed-effect population parameter estimation algorithm based on
the EM algorithm. This method allows the inclusion of explicit variab
les into the calculations, it implements an individual Bayesian parame
ter estimation procedure and also an algorithm for the conditional ass
essment of the optimal dosage regimen given a list of practical constr
aints.