What is PAGE?

We represent a community with a shared interest in data analysis using the population approach.

   Paris, France

Population pharmacokinetics of epirubicin and its main metabolite epirubicinol using NONMEM

Chanu Pascal, Tranchand Brigitte, Robert Jacques

Centre Léon-Bérard, Lab Pharmacocinétique, Lyon, France

The marked inter- and intrapatient variability of the pharmacokinetics of a number of antineoplastic agents is well known. Moreover, we can presuppose that there is, at some extent, some variability degree of cardiotoxicity and myelosuppression following an epirubicin therapy, and that this variability is in some fashion related to the administered dose of drug. In the present study, we tried to perform modeling of epirubicin, and its main metabolite epirubicinol, by using covariates in order to reduce inter- and intra patient variability. Indeed, it would be useful to predict pharmacokinetic parameters: clearance (Cl) and volume of distribution (Vd) of central compartment in order to individualize dosage regimen with minimal disturbance to the patient.

35 patients with breast cancer, Hodgkin’s disease or sarcoma entered the study (55 courses, 1 to 3 courses per patient). Each course consisted of a 5 min infusion of epirubicin. Blood samples of 5 ml were collected on heparinized tubes at 15 min, 20 min, 30 min, 50 min, 1 h 10 min, 2 h, 4 h, 24 h et 30 h after the start of the infusion. Epirubicin and its metabolite epirubicinol were assayed by HPLC on reverse phase columns with fluorescence detection.

Covariates collected were body weight (Bw) (range [45;90] kg), Age (range [26;73] years), Sex (M=1, F=2, ratio M/F = 0.37), creatinemia (SCr) (range : [40;119] µmol/l), bilirubinemia (Bili) (range : [2;19] mg/l), type of cancer (Pat) (Hodgkin’s=0 (n=9) sarcoma=1 (n=17), breast=2 (n=9).

Data analysis were performed using NONMEM version 5 under Visual-NM. For epirubicin, the best model was a three compartment model associated to a mixed error model (ADVAN 11, TRANS 4).

The objective function decreased from –4344 to –4497 after introduction of covariates. Variability in clearance decreased from 38% to 26% and in volume of distribution from 33% to 22%. Clearance and volume of distribution could be expressed as follows:

Cl=[41.0 x (1-Pat) x (2-Pat) + 26.4 x Pat x (Pat-1) + 66.3 x Pat x (2-Pat)] x [ 1 – 0.0075 x (Age – 45) ]

Vd= 10.5 x (1 – 0.33 x (Sex-1)) x (1 + 0.0078 x SCr)

Similar study has been carried out for epirubicinol using a two compartment model and first order absorption.

In conclusion, such a population model, could be used to predict pharmacokinetic parameters for patients before epirubicin therapy.