Pharmacokinetics Data Analysis of Doxorubicin Drug to Examine Variability in Patient-Specific Drug Kinetics

Pharmacokinetics-Pharmacodynamics (PK-PD), a model that integrates the time course effect of drug concentration with its pharmacological effect, is a useful mathematical tool in the preclinical development of oncology drugs; to understand and predict the pharmacological behavior of anticancer drugs. This study is on pharmacokinetics data analysis of the Doxorubicin drug to examine variability in patient-specific drug kinetics, using a model described by Young Choi et al. The proposed model employed a naïve pooled population-based PKPD modeling and revealed a higher contribution factor of Sor (PO) on overall tumor-growth inhibition than the co-administered Dox (iv) drug.

Although naïve-based population modeling can be used in designing dosing strategies for a group, when the individual variability is small, the analysis often neglects individual variability and tend to provide estimates that are less dependable. In this research, we carefully investigated the individual drug kinetics using an unpooled population method. The results help to determine the reliability of the drug kinetics obtained using the naïve method, and whether the results can be used to represent patients’ specific PK profiles. We validated our results using a widely known standard two-stage approach.

This study concludes the results obtained using the naïve pooled approach cannot be generalized to represent individual drug kinetics, due to variability in the PK profile for each patient. The result when incorporated into the proposed model may potentially increase the Dox (iv) drug contribution factor on the overall tumor growth inhibition; by strategizing dosage regime to address individual variability. The future study would be to investigate whether patients’ specific PK models designed at smaller doses could be adapted for higher dosage regimes