Aims: The aim of the present study was to develop a pharmacokinetic–pharmacodynamic (PK-PD) model to characterize the relationship between plasma doxorubicin and N-terminal pro B-type natriuretic peptide (NT-proBNP) concentrations within 48 h of doxorubicin treatment. Methods: The study enrolled 17 female patients with stages 1–3 breast cancer and receiving adjuvant doxorubicin (60 mg m–2) and cyclophosphamide (600 mg m–2) every 14 days for four cycles. In two consecutive cycles, plasma concentrations of doxorubicin, doxorubicinol, troponin and NT-proBNP were collected before infusion, and up to 48 h after the end of doxorubicin infusion. Nonlinear mixed-effects modelling was used to describe the PK-PD relationship of doxorubicin and NT-proBNP. Results: A three-compartment parent drug with a one-compartment metabolite model best described the PK of doxorubicin and doxorubicinol. Troponin concentrations remained similar to baseline. An indirect PD model with transit compartments best described the relationship of doxorubicin exposure and acute NT-proBNP response. Estimated PD parameters were associated with large between-subject variability (total assay variability 38.8–73.9%). Patient clinical factors, including the use of enalapril, were not observed to be significantly associated with doxorubicin PK or NT-proBNP PD variability. Conclusion: The relationship between doxorubicin concentration and the acute NT-proBNP response was successfully described with a population PK-PD model. This model will serve as a valuable framework for future studies to identify clinical factors associated with the acute response to doxorubicin. Future studies are warranted to examine the relationship between this acute response and subsequent heart failure. Should such a relationship be established, this model could provide useful information on patients' susceptibility to doxorubicin-induced long-term cardiotoxicity.
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© 2016 The British Pharmacological Society
- N-terminal pro-brain natriuretic peptide
- brain natriuretic peptide
- pharmacodynamic modelling