Kirsten Schorning

Kirsten Schorning works as a full professor of mathematical statistics at TU Dortmund University (Germany). Her main areas of expertise include the development of new methods for optimally designing experiments and their application, especially to complex concentration-response experiments in toxicology.

Title of keynote presentation:

Optimal design and Analysis in cytotoxicity experiments — Bridging the gap between statistics and toxicology

Abstract:

Concentration-dependent cytotoxicity experiments are frequently used in toxicology. Although it has been reported that an adequate choice of concentrations, i.e., the design, substantially improves the quality of statistical inference, a recent literature review of three major toxicological journals showed that these methods are rarely used in toxicological practice.
In this talk, we address the optimal design problem in cytotoxicity experiments from both an applied and a theoretical perspective. On the one hand, we present strategies and concrete examples for making established statistical methodology more accessible to potential users, especially biologists. On the other hand, we consider specific biological challenges in cytotoxicity experiments from the statistician’s point of view: identifying alert concentrations where a pre-specified threshold of the response variable is exceeded. We develop a model-based testing procedure for that purpose and address the corresponding optimal design problem. We construct an optimal design criterion to improve the power of the model-based testing procedure. Thus, an optimal design minimises the maximum variance of the alert concentration estimator. Optimal design theory is developed, and the results are illustrated in several examples in which the alert concentration is identified under different concentration-response relationships. In particular, it is demonstrated within a simulation study that using the optimal design results in more powerful tests for identifying alerts than using other “non-optimal” designs. In a further step, we extend the results to the situation of mixture experiments. Here, the combination of several toxic substances is considered resulting in the need of a new definition for alert concentration (combinations) and new optimal design methodology.