Variability of Skin Pharmacokinetic Data: Insights from a Topical Bioequivalence Study Using Dermal Open Flow Microperfusion

Manfred Bodenlenz, Thomas Augustin, Thomas Birngruber, Katrin I Tiffner, Beate Boulgaropoulos, Simon Schwingenschuh, Sam G Raney, Elena Rantou, Frank Sinner, Manfred Bodenlenz, Thomas Augustin, Thomas Birngruber, Katrin I Tiffner, Beate Boulgaropoulos, Simon Schwingenschuh, Sam G Raney, Elena Rantou, Frank Sinner

Abstract

Purpose: Dermal open flow microperfusion (dOFM) has previously demonstrated its utility to assess the bioequivalence (BE) of topical drug products in a clinical study. We aimed to characterize the sources of variability in the dermal pharmacokinetic data from that study.

Methods: Exploratory statistical analyses were performed with multivariate data from a clinical dOFM-study in 20 healthy adults evaluating the BE, or lack thereof, of Austrian test (T) and U.S. reference (R) acyclovir cream, 5% products.

Results: The overall variability of logAUC values (CV: 39% for R and 45% for T) was dominated by inter-subject variability (R: 82%, T: 91%) which correlated best with the subject's skin conductance. Intra-subject variability was 18% (R) and 9% (T) of the overall variability; skin treatment sites or methodological factors did not significantly contribute to that variability.

Conclusions: Inter-subject variability was the major component of overall variability for acyclovir, and treatment site location did not significantly influence intra-subject variability. These results support a dOFM BE study design with T and R products assessed simultaneously on the same subject, where T and R treatment sites do not necessarily need to be next to each other. Localized variation in skin microstructure may be primarily responsible for intra-subject variability.

Keywords: Topical bioequivalence; acyclovir; dermal open flow microperfusion; inter- and intra-subject variability; microdialysis; skin pharmacokinetics.

Figures

Fig. 1
Fig. 1
AUC values (0–36 h) of all 240 probes in 20 subjects. Top panels: Untransformed AUC values for R (8 probes per subject, left side) and T (4 probes per subject, right side). Bottom panels: Log-transformed AUC values for R (left side) and T (right side)
Fig. 2
Fig. 2
Main sources of variability for R (left side) and T (right side) derived from an ANOVA
Fig. 3
Fig. 3
Multiple linear regression analysis combined with a backward elimination technique identified skin conductance as the sole parameter among those evaluated that appeared to be consistently associated with inter-subject variability. Left side: Relationship of logAUC vs. conductance for R, right side: Relationship of logAUC vs. conductance for T
Fig. 4
Fig. 4
Distribution of the aggregated normalized intra-subject AUC values for R (0–36 h), Left side: Normalized AUC values. Right side: Normalized logAUC values
Fig. 5
Fig. 5
Comparison of logAUC values between treatment sites on the left and the right leg for R (left side) and T (right side)
Fig. 6
Fig. 6
Mean differences of logAUC values between two probes depending on their positions and their distances relative to each other. Upper panel: logAUC values for R for adjacent probes in the same treatment site (Δ 1 cm) differed by logAUC 0.46 corresponding to an arithmetic mean difference of 59%. The difference between the logAUC values increased only slightly when the two probes were in two different treatment sites (Δ 3 cm and Δ 4 cm) or at different legs (Δ leg). Lower panel: logAUC values for T between adjacent probes differed by logAUC 0.44 corresponding to an arithmetic mean difference of 55%. The factor leg did not add any variation

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