Yucheng Sheng(1), Jessica Soto(1), Mine Orlu Gul(1), Catherine Tuleu(1), Joseph F. Standing(2)
(1) School of Pharmacy, UCL (2) Institute of Child Health, UCL
Objectives: Rodent Brief-Access Taste Aversion (BATA) experiment is a common in-vivo screening tool to evaluate the taste of a drug [1]. Since the “lick number” data from BATA experiment is not normally distributed, previously published models that based on the “lick ratios” from the means are not ideal for analyzing these data. This work describes a new mixed Poisson Gaussian model development suited for BATA experiments.
Methods: The rodent BATA data were obtained from a series of experiments conducted with a well-known unpleasant taste reference compound, quinine hydrochloride dihydrate (QHD). After scrutinizing the histogram and distribution plot for each concentration of QHD, several single distribution models were tried [2,3]. As the QHD concentration rises,the proportion of first distribution will decrease and the second distribution will increase. Two mixed models, Poisson- Poisson and Poisson-Gaussian, were also tested. The proportion of the first distribution was defined as a logistic function P= EXP(EFF)/(1+EXP(EFF)) and effects(EFF) linked to QHD concentrations through the sigmoid Emax equation. Categorical VPC was used to assess model fits. Data from 3 other drugs was also used as an external validation.
Results: QHD data from BATA experiments can be well described by the new mixed distribution model with λ=2.73 for the first Poisson distribution and mean=50.5 for the second truncated Gaussian distribution. The changes among different concentrations were captured by the logistic and Emax functions. External validation and VPCs demonstrated that this new model is reasonable for all BATA data.
Conclusions: The New Mixed Poisson‐Gaussian Model is well suited for count data from rodent brief-access taste aversion (BATA) experiments .
References:
[1] Devantier HR, Long DJ, Brennan FX, et al. Quantitative assessment of TRPM5-dependent oral aversiveness of pharmaceuticals using a mouse brief-access taste aversion assay. Behav Pharmacol. (2008)19:673–82.
[2] Plan, E. L. Modeling and simulation of count data. CPT pharmacometrics Syst. Pharmacol. (2014)3:e129.
[3] Plan, E. L., Elshoff, J.-P., Stockis, A., et al. Likert pain score modeling: a Markov integer model and an autoregressive continuous model. Clin. Pharmacol. Ther. (2012)91:820–8.
Reference: PAGE 24 () Abstr 3470 [www.page-meeting.org/?abstract=3470]
Poster: Methodology - Other topics