Key result
Full PBPK models combined with Wright's renal clearance approach best predict doxorubicin plasma concentrations.
Why the study?
Doxorubicin has complex pharmacokinetics and toxicity potential, motivating the development of physiologically based pharmacokinetic models to predict its plasma concentration profiles.
PBPK models for doxorubicin were successfully developed, enabling future integration of metabolites and pharmacogenomic information.
Answers are grounded in this paper and cite their sources.
PBPK models for doxorubicin may inform dosing strategies; hypothesis-generating from case studies and requires prospective validation.
Doxorubicin (DOX) is still an important anticancer agent despite its tricky pharmacokinetics (PK) and toxicity potential. The advent of systems pharmacology enables the construction of PK models able to predict the concentration profiles of drugs and shed light on the underlying mechanisms involved in PK and pharmacodynamics (PD). By utilizing existing published data and by analysing two clinical case studies we attempt to create physiologically based pharmacokinetic (PBPK) models for DOX using widely accepted methodologies. Based on two different approaches on three different key points we derived eight plausible models. The validation of the models provides evidence that is all performing as designed and opens the way for further exploitation by integrating metabolites and pharmacogenomic information.
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Mystridis et al. (2022) studied Cancer (n=26). Doxorubicin was evaluated on Predicted vs observed AUC and Cmax of doxorubicin. Physiologically based pharmacokinetic models successfully predicted the plasma concentration profile of doxorubicin, with the full PBPK distribution model combined with Wright's renal clearance approach performing best.
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