Clinical Pharmacokinetics

, Volume 48, Issue 6, pp 359–369 | Cite as

Pharmacokinetically Based Estimation of Patient Compliance with Oral Anticancer Chemotherapies

In Silico Evaluation
  • Emilie Hénin
  • Michel Tod
  • Véronique Trillet-Lenoir
  • Catherine Rioufol
  • Brigitte Tranchand
  • Pascal Girard
Original Research Article

Abstract

Background and objectives

More and more anticancer chemotherapies are now available as oral formulations. This relatively new route of administration in oncology leads to problems with patient education and non-compliance. The aim of this study was to explore the performances of the ‘inverse problem’, namely, estimation of compliance from pharmacokinetics. For this purpose, we developed and evaluated a method to estimate patient compliance with an oral chemotherapy in silico (i) from an a priori population pharmacokinetic model; (ii) with limited optimal pharmacokinetic information collected on day 1; and (iii) from a single pharmacokinetic sample collected after multiple doses.

Methods

Population pharmacokinetic models, including estimation of all fixed and random effects estimated on a prior dataset, and sparse samples taken after the first dose, were combined to provide the individual POSTHOC Bayesian pharmacokinetic parameter estimates. Sampling times on day 1 were chosen according to a D-optimal design. Individual pharmacokinetic profiles were simulated according to various dose-taking scenarios.

To characterize compliance over the n previous dosing times (supposedly known without error), 2n different compliance scenarios of doses taken/not taken were considered. The observed concentration value was compared with concentrations predicted from the model and each compliance scenario. To discriminate between different compliance profiles, we used the Euclidean distance between the observed pharmacokinetic values and the predicted values simulated without residual errors.

This approach was evaluated in silico and applied to imatinib and capecitabine, the pharmacokinetics of which are described in the literature, and which have quite different pharmacokinetic characteristics (imatinib has an elimination half-life of 17 hours, and α-fluoro-β-alanine [FBAL], the metabolite of capecitabine, has an elimination half-life of 3 hours). 1000 parameter sets were drawn according to population distributions, and concentration values were simulated at several timepoints under various compliance patterns to compare with the predicted ones. In addition, several simulation scenarios were run in order to explore the impact of the quality of the error model, interoccasion variability (IOV), error in the number of pills taken, and the performance of the compliance estimation method.

Results

The best compliance estimate was obtained with pharmacokinetic samples taken 5 hours after the last dose. Performance of the method varied between simulation scenarios. In both the imatinib and capecitabine basic simulations, patient compliance was correctly estimated on the two last scheduled doses (with better results for imatinib). The magnitude of the error model also had a great impact on the quality of the compliance estimate.

Conclusions

We highlight the effect of three parameters on the quality of compliance estimates based on limited pharmacokinetic information: the plasma elimination half-life, interdose interval and magnitude of the error model. Nevertheless, the pharmacokinetic method is not informative enough and should be used with electronic monitoring, which provides additional information on compliance. Our method will be used in a future phase IV clinical trial where the relationships between compliance, efficacy and tolerability will be assessed.

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Copyright information

© Adis Data Information BV 2009

Authors and Affiliations

  • Emilie Hénin
    • 1
  • Michel Tod
    • 1
  • Véronique Trillet-Lenoir
    • 1
    • 2
  • Catherine Rioufol
    • 1
    • 3
  • Brigitte Tranchand
    • 4
  • Pascal Girard
    • 1
  1. 1.Faculté de Médecine Lyon SudUniversité Lyon 1, EA3738, CTOOullinsFrance
  2. 2.Service d’Oncologie Médicale, Centre Hospitalier Lyon SudHospices Civils de LyonPierre-BéniteFrance
  3. 3.Unité de Pharmacie Clinique Oncologique, Centre Hospitalier Lyon SudHospices Civils de LyonPierre-BéniteFrance
  4. 4.Centre Léon BérardLyonFrance
  5. 5.Faculté de Médecine Lyon-SudEA 3738, CTOOullins CedexFrance

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