Speaker
Description
Evaluating a response variable in relation to exposure time or dose is a pivotal objective in the assessment of a compound's effect, particularly when determining toxicity in pre-clinical research or pharmacokinetics in clinical trials. The determination of an alert, such as the EC50 value, at which a pre-specified threshold of the response variable is crossed, is an important tool for the evaluation process. In practice, response data might be available for combinations of different exposure times and doses and the alert in relation to both is of interest. In this case, it is crucial to use all available information and extrapolate between cases to ensure the optimal utilisation of the data.
In this talk, we propose a parametric method that allows the determination of alert–doses for a fixed time, even in the absence of measurements for the specific time, and vice versa, or to discern the full time–dose–alert relationship using all available data. This is achieved by fitting a parametric time–dose–response model and constructing either a confidence band for the two-dimensional curve given a fixed time or dose or a confidence plane for the three-dimensional model fit. Both are derived by a two-step bootstrap approach. It is summarised in terms of a hypothesis test, that can be adjusted to accommodate a variety of alert types. Rejecting the null hypothesis means detecting an alert–dose/time, or the time–dose–alert relationship. The initial model fit is achieved by the flexible framework of a Generalised Additive Model for Location, Scale and Shape (GAMLSS), which is then used to generate the bootstrap samples. This offers the possibility to account for a plethora of complex three-dimensional data structures.
We demonstrate the validity of our approach through a simulation study and present an application to data from a study investigating the relevance of the exposure duration on cytotoxicity in primary human hepatocytes.
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