Abstract
Population studies of the pharmacokinetics or pharmacodynamics of drugs help us learn about the variability in drug disposition and effects, information that can be used to treat future patients at safe and effective doses. We present a new approach to population modeling based on a weighted mixture of normal distributions having random weights and means. This method allows estimation of underlying continuous population distributions without prespecifying the parametric form or shape of these probability distributions. Additionally, this method can carry out nonparametric regression of pharmacokinetic or dynamic parameters on patient covariates while estimating the underlying distributions. Two examples illustrate the method and its flexibility.
Original language | English (US) |
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Pages (from-to) | 209-233 |
Number of pages | 25 |
Journal | Journal of Pharmacokinetics and Biopharmaceutics |
Volume | 25 |
Issue number | 2 |
DOIs | |
State | Published - 1997 |
Externally published | Yes |
Keywords
- Bayesian analysis
- Dirichlet process
- Kernel density estimation
- Mixture models
- Nonparametric regression
ASJC Scopus subject areas
- General Pharmacology, Toxicology and Pharmaceutics
- Pharmacology (medical)