One-third of the U.S. population is now classified as obese (body mass index ≥ 30 kg/m
2) (
5). Although the prevalence of obesity has increased over the past 2 decades, studies that evaluate the disposition of antimicrobials in this population are scant (
6,
12). The U.S. Food and Drug Administration (FDA) does not presently recognize obese patients as a special population, and thus, no specific guidance to evaluate drug disposition in this population exists (
6). As a result, clinical trials in the early phases of drug development often exclude obese subjects. Despite this exclusion, drugs are ultimately used in a broader population than that studied in controlled trials. Anecdotal evidence suggests that clinicians may arbitrarily adjust doses on the basis of TBW. This approach may be reasonable for drugs with linear pharmacokinetics and PK parameters that are weight dependent. However, this approach may be unreasonable for drugs like voriconazole with nonlinear pharmacokinetics: for this drug, doubling the dose leads to greater than twice the exposure. Hence, the possibility of under- or overdosing voriconazole in obese subjects is an unfortunate reality given the paucity of clinical pharmacokinetic data in this population.
The current study was designed to provide clinical pharmacokinetic data in a small cohort of obese subjects. We demonstrated that the volume of distribution and clearance of voriconazole between obese and nonobese subjects were indistinguishable, in spite of marked differences in TBW. The similar pharmacokinetic estimates were reflected in highly comparable estimates of AUC0–τ, Cmax, and Cmin between weight groups, especially with the 300-mg twice-daily maintenance dosing schedule. For the 200-mg twice-daily regimen, the mean plasma exposures were numerically higher in the obese group relative to the nonobese group, contrary to what you would expect if weight influenced the pharmacokinetics of an agent. Although a higher mean exposure profile was noted in the obese group, the difference was not statistically significant and perhaps not clinically relevant, as the AUC0–τ distributions were largely overlapping.
Several important inferences can be drawn from the similar pharmacokinetic profiles observed between weight groups. Although voriconazole is a relatively lipophilic compound, the comparable volumes of distribution suggest that it does not necessarily distribute to adipose tissue differently in obese versus nonobese individuals. Further exploration of this theory is warranted through the conduct of noninvasive (
19F magnetic resonance spectroscopy) or semi-invasive (microdialysis) studies in obese subjects treated with voriconazole (
2). The similar clearances indicate that the clearance capacity of voriconazole does not directly scale to TBW. Exploration of ABSDs demonstrated this to be the case, and LBW was found to be a better scalar than TBW. However, neither weight parameter truly predicted (
r2 < 0.5) the variability in voriconazole exposure. The lack of a clinically meaningful relationship in the ABSD analysis indicates that there are more important factors than weight in accounting for both inter- and intrapatient variability in exposure profiles.
Although weight was not found to be an important pharmacokinetic covariate for voriconazole, a strong linear relationship between voriconazole
Cmin values and AUC
0–τ values was noted. This has very practical implications for clinicians. In a neutropenic murine model of disseminated candidiasis, a free 24-hour AUC/MIC ratio of 20 to 25 has been demonstrated to be predictive of treatment success (
1). Similarly, Mavridou and colleagues have demonstrated the effectiveness of voriconazole to be closely related to free 24-hour AUC/MIC values in a neutropenic murine model of disseminated aspergillosis (
9). Consequently, in patients a simple function such as 16.09 ·
Cmin = AUC
0–τ could be used to derive a practical clinical estimate of AUC
0–τ. This translation may aid future research groups to identify a clinical AUC/MIC target range that can be used to validate the current preclinical AUC/MIC targets outlined above. Again, adoption of such an approach requires refinement of the estimate of this coefficient (16.09) through analyses of larger data sets. At a minimum, our study at least reveals that the clinical measurement of
Cmin values may be easily transformed to the more robust PK parameter of AUC in order to better predict clinical effect. This is especially important because a specific therapeutic range for voriconazole
Cmin values (for any drug, for that matter) is likely to remain elusive. Lewis has eloquently framed the rationale of this premise by guiding clinicians to dissociate the concept of a therapeutic range as “an absolute entity; rather, as a concept of probability” (
8).
In conclusion, this pilot study provides, for the first time, a glimpse into the disposition of voriconazole in an emerging special population of obese individuals. The knowledge gained from the current study should be utilized to improve population pharmacokinetic models of voriconazole. Oral dosing of voriconazole should not be based on TBW, especially in obese patients, given the risk of disproportional exposure and toxicity. Although our study did not evaluate intravenous dosing of voriconazole, dosing this antifungal solely on the basis of TBW will also lead to disproportional exposure and toxicity in obese patients. A reappraisal of weight-based voriconazole dosing practices in adults is needed. Additional prospective trials in obese patients with invasive fungal infections who are treated with voriconazole are necessary to validate the conclusions of our study.