Distinguishing animal subsets in toxicokinetic studies: comparison of non-linear mixed effects modelling with non-compartmental methods

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Abstract
The purpose of this study was to compare the ability of non-compartmental analysis and compartmental mixed effects modelling (MEM) to determine the existence and magnitude of exposure differences (i.e. exposure ratio estimates) between subsets of animals during destructive toxicokinetic studies. Data from five toxicokinetic studies of an experimental compound were analysed using a linear trapezoidal calculation of the area under the curve (non-compartmental analysis) or modelled using MEM. With the non-compartmental method the Bailer-Satterthwaite approximation was used to construct confidence intervals around the exposure estimates of each subset of animals and these were used to determine if exposure differed between the subsets. The MEM analyses were performed on the full datasets and on datasets with arbitrary reductions in the number of animal replicates. With MEM, additional model parameters were used to differentiate between subsets of animals, and were incorporated only if they were justified statistically. Estimates of the existence and magnitude of exposure differences between animal subsets were similar with the two techniques. The MEM analyses were influenced only marginally by substantial reductions in the number of animals studied and were less compromised by extremely limited or unbalanced data. These analyses show that MEM and non-compartmental methods are similarly effective at detecting exposure differences between animal subsets in toxicokinetic studies. Estimates provided by both methods were influenced by the degree of variance in the data. These results support the proposition that it may be possible to reduce the number of animals employed in toxicokinetic studies if MEM is used.

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