Physiologically based pharmacokinetic (PBPK) modeling
has increasingly
been employed in dermal drug development and regulatory assessment,
providing a framework to integrate relevant information including
drug and drug product attributes, skin physiology parameters, and
population variability. The current study aimed to develop a stepwise
modeling workflow with knowledge gained from modeling in vitro skin
permeation testing (IVPT) to describe in vivo exposure of metronidazole
locally in the stratum corneum following topical application of complex
semisolid drug products. The initial PBPK model of metronidazole in
vitro skin permeation was developed using infinite and finite dose
aqueous metronidazole solution. Parameters such as stratum corneum
lipid–water partition coefficient (Ksclip/water)
and stratum corneum lipid diffusion coefficient (D
sclip) of metronidazole were optimized using IVPT data from simple aqueous solutions (infinite) and MetroGel (10 mg/cm2 dose application), respectively. The optimized model, when
parameterized with physical and structural characteristics of the
drug products, was able to accurately predict the mean cumulative
amount permeated (cm2/h) and flux (μg/cm2/h) profiles of metronidazole following application of different
doses of MetroGel and MetroCream. Thus, the model was able to capture
the impact of differences in drug product microstructure and metamorphosis
of the dosage form on in vitro metronidazole permeation. The PBPK
model informed by IVPT study data was able to predict the metronidazole
amount in the stratum corneum as reported in clinical studies. In
summary, the proposed model provides an enhanced understanding of
the potential impact of drug product attributes in influencing in
vitro skin permeation of metronidazole. Key kinetic parameters derived
from modeling the metronidazole IVPT data improved the predictions
of the developed PBPK model of in vivo local metronidazole concentrations
in the stratum corneum. Overall, this work improves our confidence
in the proposed workflow that accounts for drug product attributes
and utilizes IVPT data toward improving predictions from advanced
modeling and simulation tools.