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


2002
   Paris, France

Population Pharmacokinetic Analysis of Zarnestra Using Data From Phase I Clinical Trials

Juan Jose Perez Ruixo(1); Vladimir Piotrovsky(1); Kenneth H. Cowan(2); Louis Weiner (3); Cornelis J.A. Punt (4); Martine Piccart (5).

(1)Johnson & Johnson Pharmaceutical R & D, Beerse, Belgium. (2) National Cancer Institute, Bethesda, MD. (3) Fox Chase Cancer Center, Philadelphia, PA. (4) University Hospital St. Radboud, Nijmegen, Belgium. (5) Institut J. Bordet, Brussels, Belgium.

Objective: To perform a population pharmacokinetic (PK) analysis of the phase I clinical trial data of a new anticancer drug, after single and multiple doses of different drug formulations in healthy volunteers as well as cancer patients.

Patients and Methods: Data from 12 healthy volunteers and 129 patients included in 6 phase I clinical trials were pooled. Subjects were treated with ZarnestraTM (orally and intravenously). Three different oral formulations (solution, capsule and tablet) were administered as a single dose or as multiple doses (b.i.d) in a range dose between 25 and 1300 mg. Data for 1, 2 and 24 hours intravenous infusions for different dose levels were also available. Full PK profiles were scheduled at least in two occassions for every patient. Moreover, trough levels were obtained for multiple dose regimen. A total of 3129 plasma concentrations were obtained and analyzed by a validated assay method.

An open three-compartment linear disposition model with sequential zero and first order absorption process and lag time was fitted to the data. Interindividual and interoccassion variabilities were implemented through exponential error model. Measured concentrations and model predictions were transformed into logarithms. The error model was additive and included 2 variances to account for the residual variability of full PK profiles and trough levels. The estimation of the population parameters was done with the first order approximation method implemented in NONMEM V software.

Body size parameters (weight, lean body mass, ideal body weight, body mass index, and body surface area), renal (creatinine clearance and glomerular filtration rate) and liver function tests (AST, ALT, AP, LDH and total bilirubine), trial, drug formulation, target population and disease stage were tested as covariates by graphical exploration followed by (one-by-one) the forward stepwise inclusion procedure. Finally, the significance of covariate fixed effects was tested by backward elimination. The p-value for retaining a covariate in the model was 0.01 at 1 degree of freedom, c 2 distribution.

Results: The pharmacokinetics of the drug was proved to be dose- proportional in the wide dose range. Population PK parameters after tablet administration are shown in the table 1. Healthy volunteers have a higher clearance and volume of distribution in the central and peripheral compartments, as well as a higher absorption rate and a lower duration of the zero-order process than patients in the target population. Rate and extent of absorption are significantly different between drug formulations. AST is associated with the decrease in plasma clearance, and volume of distribution in peripheral compartment increased with body weight.

Table 1. Population pharmacokinetics parameters of Zarnestra after IV and tablet administration.

Parameter

Mean (CV, %*)

IIV (CV, %)

IOV (CV, %)

CL (L/h)

22.6 (5.13)

33.32 (20.72)

26.55 (29.58)

Vc (L)

66.4 (7.95)

43.01 (36.22)

-

Q2 (L/h)

3.49 (14.13)

67.23 (33.63)

122.88 (45.17)

V2 (L)

105 (10.19)

87.52 (32.51)

-

Q3 (L/h)

20.7 (30.14)

-

-

V3 (L)

27.6 (15.07)

-

-

Ka (1/h)

1.21 (15.12)

146.29 (58.88)

110.45 (24.34)

D (h)

0.84 (3.26)

93.43 (49.37)

15.62 (50.41)

F (%)

0.35 (5.19)

48.06 (18.70)

50.20 (34.60)

Lag (h)

0.08 (0.09)

285.66 (75.37)

389.87 (35.99)

* CV (%): Coefficient of variation

Conclusion: A population PK approach is useful tool to integrate the knowledge gathered in phase I studies. The model developed will help in dose adaptation and will further be used in PK/PD modelling of therapeutic outcomes and adverse events.



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