IV-17

Design of preclinical experiments: an example in chemotherapy-induced myelosupression

Emma C. Martin (1), Leon Aarons (1) and James W. Yates (2)

(1) Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, The University of Manchester, United Kingdom, (2) AstraZeneca, Innovative Medicines, Oncology, Modelling and Simulation, Alderley Park UK

Objectives: To investigate a new preclinical study design (referred to as a compact design) that removes the need for satellite animals for the collection of pharmacokinetic (PK) data, by characterising the PK in the main study animals, taking no more than one sample in 24 hours to build up a full profile over the course of the study.

Methods: The design’s performance was tested through a simulation study, based on drug concentration and neutrophil count data following administration of chemotherapy in rats. One hundred datasets were simulated from a model based on available data, using both the compact design and a traditional design using satellite animals. The effect of the compact design on parameter and variance estimates following the fitting of a PKPD model was investigated, as well as the potential effect of inter-occasion variability (IOV).

Results: The compact design performed equally well, and had little impact on parameter estimates, or variation estimates, indicating that it may be a preferable alternative to traditional satellite designs whilst using fewer animals. When IOV was ignored during analysis the PK model parameters remained well estimated, however the inter-individual variation (IIV) and residual errors were inflated. Ignoring IOV in the neutrophil model caused some bias in parameter estimates, as well as inflating the inter-individual variation and residual error. Estimating IOV improved parameter estimates, but IIV and IOV could not be well estimated simultaneously using the compact design.

Conclusions: Using the proposed compact design removes the need for a satellite group, reducing the number of animals, without impacting the ability to model the data. If IOV is suspected, caution should be used, as the variation in the PK model can be inflated.

Reference: PAGE 24 (2015) Abstr 3493 [www.page-meeting.org/?abstract=3493]

Poster: Methodology - Study Design