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Parametric and non-parametric prediction intervals based phase II control charts for repeated bioassay data.
L A Hothorn1, D Gerhard, M Hofmann
1Leibniz University Hannover, Institute of Biostatistics, Herrenhauser Str.2, D-30419 Hannover, Germany. hothorn@biostat.uni-hannover.de
Summary
Phase II control charts enhance bioassay quality control using potency measurements. Robust, non-parametric prediction intervals, including winsorization methods, are proposed for reliable future re-test intervals, even with outliers.
Area of Science:
- Biostatistics
- Pharmaceutical Quality Control
- Industrial Quality Control
Background:
- Bioassay quality control is crucial for reliable results.
- Industrial quality control methods, like phase II control charts, can be adapted for bioassays.
- Potency is the key metric, with one value per bioassay run.
Purpose of the Study:
- To adapt phase II control charts for bioassay quality control.
- To develop and evaluate parametric and non-parametric prediction intervals for bioassay re-tests.
- To propose robust prediction intervals addressing outliers and small sample size limitations.
Main Methods:
- Application of phase II control charts to bioassay potency data.
- Description of parametric and non-parametric prediction intervals.
- Development of robust prediction intervals using winsorization.
- Provision of R-functions for implemented methods.
Main Results:
- Established methods for quality control intervals in repeated bioassays.
- Identified limitations of non-parametric prediction intervals with small sample sizes and outliers.
- Demonstrated the utility of robust prediction intervals based on winsorization for improved reliability.
Conclusions:
- Phase II control charts offer a viable framework for bioassay quality control.
- Robust prediction intervals are essential for handling real-world bioassay data, including outliers.
- The proposed methods and R-functions support enhanced quality control in bioassay development and manufacturing.
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