B. Vrijens and E. Goetghebeur
University of Ghent, Department of Applied Mathematics and Informatics, Krijgslaan 281-S9, B-9000 Ghent, Belgium
Population pharmacokinetics (PK) and pharmacodynamics (PD) study the variability between individuals in drug concentration and pharmacological effect when standard dosage regimens are assigned. It constitutes a scientific bases for the determination of the optimal dosage of a new drug.
Population PK/PD works with relatively sparse data, but has the great advantage of enabling the study of a representative sample of patients who take the drug over a possibly long period of time.
We expose the problem of biased PK/PD estimators in the presence of partial compliance with assigned treatment as it occurs in practice. We propose a solution by using timing explicit hierarchical nonlinear models and accurate information on a number of previous dose timings.
Surprisingly, we see that not only bias is reduced but higher precision is retrieved from the same number of data points when it is possible to observe non-selective irregular drug intake times in well controlled studies.
We apply methods proposed by Mentre et al. (1997) to investigate the information matrix for hierarchical non-linear models, it is confirmed that a substantial gain can be expected by observing irregular drug intake.
Intuitively this is explained by the fact that regular takers experience a relatively small range of concentration which makes it hard to estimate any deviation from linearity in the effect model. We conclude that estimators of PK/PD parameters can benefit greatly from information that enters through greater variation in the drug exposure process.
Reference: PAGE 9 (2000) Abstr 90 [www.page-meeting.org/?abstract=90]
Poster: oral presentation