2016 - Lisboa - Portugal

PAGE 2016: Drug/Disease modeling - Other topics
Coen van Hasselt

The proof is in the pee: Population asparagus urinary odor kinetics.

J. G. Coen van Hasselt(1), Jeroen Elassaiss-Schaap(1,2), Anuradha Ramamoorthy(3), Brian M. Sadler(4), Sreeneeranj Kasichayanula(5), Yin Edwards(6), Piet H. van der Graaf(1,7), Lei Zhang(1), John A. Wagner(8)

(1) Leiden University, Leiden, Netherlands; (2) PD-Value BV, Houten, Netherlands; (3)Food and Drug Administration, Silver Spring, MD, USA; (4)ICON, Gaithersburg, MD, USA; (5)Amgen, Thousand Oaks, CA, USA; (6)ICON plc, Marlow, UK; (7)Certara, Canterbury, UK; (8)Takeda Pharmaceuticals International Co., Cambridge, MA, USA.

Objectives: Inter-individual variability (IIV) in production and perception of odorous urine after eating asparagus has been reported [1]. We conducted a “first-ever” clinical study with consenting 2014 and 2015 ASCPT annual meeting attendees to characterize asparagus urinary odor kinetics. The objective of this study was to characterize time-response, dose-response dynamics and half-life (t½) of urinary asparagus odor perception after receiving a single variable dose of asparagus.

Methods: Consenting subjects were randomized to eat a specific number (dose) of asparagus spears. Subjects were asked to report their urinary odor perception for until no noticable odor was perceived on case report forms. Odor perception was reported as a subjective score on a scale of 0-6 (0=no odor to 6=offensive odor). A mixed effect proportional odds K-PD model was used to associate dose with odor scores, and to estimate a t½ for dose received. A mixture model was used to estimate the proportion of responders (PRESP) in terms of perceiving and/or producing the odor in urine. An asparagus dose-response slope parameter was considered in the proportional odds model as additional term.

Results: Data was pooled from a pilot study (n=10; dose 0, 5, 10, 15 spears), and the main study (n=81; dose 0, 3, 6, 9 spears). Out of these 91 subjects, 9 reported no detectable odor. A half-life of 3.9 h (RSE, relative standard error, 44%) was estimated. A dose-response slope term was identified with good precision (22%), and was found to be equal for different score levels. For scores 4 and 5, a single coefficient was estimated due to insufficient data. IIV was estimated for t½ and for baseline variability of the score for responders. IIV on the t½ and baseline parameter was large: 43.4 CV% and 84.3 CV% respectively. PRESP was estimated at 92.4% (RSE 12%). A correlation between age and t½ was present but could not be reliably included in the model.

Conlusion: Dose-response dynamics of asparagus urinary odor score and time course data could be adequately characterized using the developed model. There was large IIV in asparagus t½ and baseline score. This study design can be used as a demonstration project for population kinetics studies in many settings including schools. We plan to build a tutorial and an open sourced database with the potential to link results through “crowd sourcing” and allowing other researchers to add their data and build the database.



References:
[1] Drug Metab Dispos. 2001 Apr;29(4 Pt 2):539-43.


Reference: PAGE 25 (2016) Abstr 5717 [www.page-meeting.org/?abstract=5717]
Poster: Drug/Disease modeling - Other topics
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