A population PK-PD method for categorical data analysis of progesterone antagonist activity in the rabbit McPhail’s model
Francesca Del Bene, Massimiliano Germani, Maurizio Rocchetti, Alex De Giorgio-Miller, Nick Pullen, Peter Bungay, Chris Kohl & Piet van der Graaf
ACCELERA - Nerviano Medical Sciences (Italy) & Pfizer Global Research & Development (United Kingdom)
Objectives: The McPhail's test [1] of endometrial differentiation and thickening is a commonly used method for preclinical assessment of progesterone antagonist activity in vivo [see, for example, [2]). However, as far as we know, a method for integrated PK/PD analysis that allows for a comparison of the dynamic effects of compounds in this model has not yet been described, possibly due to the categorical nature of the endpoint generated. Therefore, the objective of this study was to develop an ordered categorical population PK-PD analysis methodology for describing the effect of progesterone antagonists in a McPhail's preclinical model of endometrial thickening. Three compounds were tested and analysed for this purpose.
Methods: The efficacy of three compounds was evaluated after repeated administrations (once or twice daily for four consecutive days) of different dose levels (n=4to four rabbits/dose). McPhail's test results were expressed as a score from 0-4 depending on the degree of endometrial tissue differentiation and thickening. Different sparse pharmacokinetic sampling procedures were adopted for the three compounds, dividing the animals into two groups of two rabbits each with a number of samples ranging from four to eleven depending on the investigated compound.
Results: Due to the limited number of animals available, the efficacy data, expressed as McPhail's score, were reduced to a binary PD variable with value equal 1 and 0 according to a McPhail's score ≤ 2 and >2, respectively. Subsequently, for each compound, the individual cumulative unbound AUC values obtained from population PK analysis were related to the PD variable applying a logistic regression model implemented in NONMEM in order to estimate the probability of observing an outcome less or equal than 2.With the aim of minimizing the number of parameters and enhancing statistical power, the PK-PD categorical model was further modified and implemented in Matlab for performing a joint analysis of all the compounds. The AUC values related to the 80% and 90% of probability to obtain the outcome of interest (McPhail's score ≤ 2) were calculated and showed for each compound.
Conclusions: We have developed a method that allows for a simultaneous analysis and comparison of PK-PD relationships of series of compounds in the McPhails model of progesterone antagonist activity. The method has been implemented in NONMEM and Matlab and should provide a quantitative basis for the rational selection of preclinical candidates for further clinical development.
References:
[1] McPhails, M.K. (1934). J. Physiol. 83: 145-156.
[2] Kurata, Y. et al. (2005). J. Pharmacol. Exp. Ther. 313: 916-920.