Eline van Maanen (1), Oliver Ackaert (1), Nelleke Snelder(1), Kirsten Bergmann (1), Carla Maciag (2), Mike Quirk (2), Carin Wallsten (3), and Bart Ploeger (3)
(1) LAP&P Consultants BV, Leiden, The Netherlands; (2) CNSP iMed, AstraZeneca R&D Wilmington, Delaware, USA; (3) Modelling & Simulation, CNSP iMed, AstraZeneca R&D, Södertälje, Sweden
Objectives: Many biological variables are not normally distributed, which makes visual data exploration challenging and affects the performance of non-linear mixed effect modeling. Our objective was to develop a data transformation method to facilitate analysis of non-normally distributed data. The effect of the low-trapping, NMDA channel blocker, AZD6765, on the time that prenatally stressed (PNS) animals spent in the open arms of an elevated plus maze (EPM) is used as a case study. The EPM is a plus-shaped maze with 2 open and 2 closed arms. An increase in exploration of the open arms by PNS rats may reflect antidepressant effects.
Methods: Dose ranging, continuous data obtained in the EPM test with male PNS rats receiving a single dose of AZD6765 or saline ip were used with 5-6 repeated measurements up to 9 weeks postdose. The saline treatment group consisted of a non- PNS and a PNS subgroup. An iterative data transformation procedure was followed by calculating: 1) the cumulative sum of time in open arms of the EPM at each time point; 2) the natural logarithm of cumulative sum of time in open arms at each time point. For the analysis of the transformed data, a stepwise modeling approach was followed: 1) the baseline curve (non-PNS) was described; 2) PNS effect on baseline curve was evaluated; 3) the drug effect was assessed.
Results: After the first step in the data transformation, a consistent trend in the data for all treatment groups was obtained: the number of 0 values in the data was reduced and the variability in the data was decreased. Following the second step a close to normal distribution was obtained and a comprehensible PNS effect and dose response was observed. Model development using the transformed data resulted in an adequate description of the dose-response relationship and the observed variability. Potency and efficacy of AZD6765 were quantified.
Conclusion: Data transformation calculations enable data to be converted into a more readily available format that provides a visual representation and allows additional analysis. Data transformation can be applied iteratively and each transformation can produce a different perspective that may provide greater insight and understanding. With the data transformation procedure presented here, potency and efficacy of AZD6765 in the EPM data could be estimated.
Reference: PAGE 21 (2012) Abstr 2436 [www.page-meeting.org/?abstract=2436]
Poster: CNS