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Discrepancies in pharmacokinetic analysis results obtained by using two standard population pharmacokinetics software
Yaron Finkelstein1, Alejandro A Nava-Ocampo, Tal Schechter
1Division of Clinical Pharmacology and Toxicology, Department of Pediatrics, The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario M5G1X8, Canada. yfinkel@yahoo.com
Fundamental & Clinical Pharmacology
|March 10, 2009
Summary
Population pharmacokinetic (PK) modeling software can yield different results. Comparing p-pharm and saam ii for doxorubicin PK analysis showed significant parameter discrepancies, highlighting the need for cross-validation.
Area of Science:
- Pharmacokinetics
- Computational Biology
- Pediatric Oncology
Background:
- Standard software packages for population pharmacokinetic (PK) modeling exist.
- These programs may differ in their underlying algorithms for modeling plasma concentrations over time.
Purpose of the Study:
- To compare population PK parameters derived from two distinct software packages, p-pharm and saam ii.
- To analyze a dataset of doxorubicin serum concentrations from pediatric cancer patients.
Main Methods:
- Utilized a two-compartment intravascular PK model to fit plasma drug concentrations over time.
- Applied both p-pharm and saam ii software packages to the same dataset.
- Compared the resulting population PK parameters, including volume of distribution (Vd) and elimination half-life (t(1/2)beta).
Main Results:
- Substantial differences were observed in population PK parameters between p-pharm and saam ii.
- Volume of distribution (Vd) was approximately five times larger with saam ii (9.6 L/kg) compared to p-pharm (2.0 L/kg).
- Elimination half-life (t(1/2)beta) was significantly longer with p-pharm (206.9 h) versus saam ii (7.7 h).
Conclusions:
- Population PK parameter estimates can vary considerably depending on the software used.
- Cross-validation of PK modeling results using different software packages is recommended, particularly when encountering unexpected parameter values.
- This emphasizes the importance of software selection and validation in population PK analysis.
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