Experimental design

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The Mouse Bioassay for Diarrhetic Shellfish Poisoning: A Gross Misuse of Laboratory Animals and of Scientific Methodology

Robert D. Combes

The UK shellfish industry has recently been affected by the statutory closure of several cockle beds, following the detection of samples causing rapid and severe reactions in the regulatory approved test for diarrhetic shellfish poisoning (DSP) toxins, the mouse bioassay (MBA). It is contended that these socalled atypical results are due to procedural artefacts of the MBA; so far, several studies have failed to identify their cause. This paper critically assesses the development, regulatory use and methodological deficiencies of the MBA. It also discusses how testing for DSP toxins could and should have been improved and made more humane by applying the Three Rs concept of Reduction, Refinement and Replacement, and by the proper validation of the test method used. It is concluded that the MBA should not have been developed for the routine screening of shellfish samples, as it has a substantially severe endpoint and is not used as part of a tiered-testing strategy with non-animal methods. Moreover, during the UK monitoring programme for DSP toxins, the assay has been used without an optimised and universal protocol, and apparently without due regard to the principles of basic scientific methodology. In view of this, the atypical results obtained for cockle samples cannot be relied on as evidence of a human health hazard. It is recommended that the use of the MBA should be discontinued as soon as possible, in favour of other methods, especially those involving non-animal techniques. In the short-term, these methods should be based on analytical chemical detection systems and the essential availability of the relevant pure toxin standards. The lack of any known toxins in samples should be taken as evidence of lack of contamination. The suitability of the existing non-animal methods needs to be assessed as a matter of urgency. It is crucial that all new methods should be properly validated, and that their acceptability for their stated purposes should be endorsed by recognised criteria and validation centres, before being recommended to, or required by, regulatory agencies. In this way, the possibility that scientifically unsuitable methods will once again be used for monitoring for the contamination of shellfish with toxins can be avoided. This gross misuse of laboratory animals and ill-judged application of science should never be allowed to occur again.
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The FRAME Reduction Steering Committee: Reflections on a Decade Devoted to Reducing Animal Use in Biomedical Science

Michelle Hudson and Bryan Howard

Established in 1998, the FRAME Reduction Committee (FRC) (now the FRAME Reduction Steering Committee [FRSC]) has continued to pursue its aim of reducing the number of animals used in biomedical science. Through its expertise in statistics, experimental design, animal welfare and research on alternatives, it has contributed to raising awareness of the need for reduction and the means of achieving and demonstrating it. In recognising the need for training of scientists to appreciate and understand the concept of reduction, the FRSC has organised dedicated workshops and training schools. Some of the Committee’s major achievements are described, and, bearing in mind the current year-on-year increases in the number of scientific procedures on animals, its future activities are outlined.
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Planning for Reduction

Rose Gaines Das, Derek Fry, Richard Preziosi and Michelle Hudson

Reduction is one of the Three Rs which can be readily achieved in practice. This can be done by careful consideration of the experimental strategy and the implementation of good experimental design. Moreover, strategic planning leads to ‘best’ scientific practice and can have a positive impact on both refinement and replacement. The FRAME Reduction Steering Committee has developed a flow chart for an overall strategy for planning and conducting biomedical research. This, and important planning considerations for each of the steps proposed, are discussed. The strategy involves taking an initial overview and undertaking related background research, then planning a sequence of experiments expected to give satisfactory results with the least animal use and minimal severity, choosing an efficient design for each experiment in the sequence, reviewing the results of one experiment before progressing to the next, and conducting an overall analysis at the end of the programme. This approach should minimise animal use and maximise the quality of the resultant scientific output.
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More is Less: Reducing Animal Use by Raising Awareness of the Principles of Efficient Study Design and Analysis

Bryan Howard, Michelle Hudson and Richard Preziosi

Good experimental design and the appropriate use of statistical tests form the corner stone of high-quality scientific research. This is especially important when the experiments involve the use of laboratory animals, to ensure that their use is appropriate and that the minimum number of animals will be used that will provide data which are sufficiently statistically-sound to meet the objectives of the study. One way to raise awareness of the importance of efficient study design and analysis is to provide training courses. This paper reports the views of participants at two such training schools, with reference to why they felt that attendance was necessary and how effective they felt the experience had been. The implications of the responses are discussed, and considerations for future training events are noted.
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Improving the Design and Analysis of Animal Experiments: A Personal Odyssey

Michael F.W. Festing

Everybody’s career depends on many chance factors: the people one meets, the opportunities which are available, or the state of a scientific discipline. Mine is no exception. I started out in agriculture, obtained a PhD in quantitative genetics, and spent most of my career concerned with the use of animals in biomedical research. Soon after I joined the Medical Research Council Laboratory Animals Centre in 1966, as their geneticist in charge of many species and strains of laboratory animals, I was introduced to Russell and Burch’s book, The Principles of Humane Experimental Technique. It had a significant effect on my future, which has encompassed two related themes: the need for better experimental design, and the conviction that, in most research, inbred strains of rats and mice should normally be used in preference to genetically undefined outbred stocks. The establishment of the FRAME Reduction Committee has helped me to pursue both of these, although toxicologists continue to ignore basic design principles, by using outbred stocks.
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Guidelines for the Design and Statistical Analysis of Experiments in Papers Submitted to ATLA

Michael F.W. Festing

In vitro experiments need to be well designed and correctly analysed if they are to achieve their full potential to replace the use of animals in research. An “experiment” is a procedure for collecting scientific data in order to answer a hypothesis, or to provide material for generating new hypotheses, and differs from a survey because the scientist has control over the treatments that can be applied. Most experiments can be classified into one of a few formal designs, the most common being completely randomised, and randomised block designs. These are quite common with in vitro experiments, which are often replicated in time. Some experiments involve a single independent (treatment) variable, whereas other “factorial” designs simultaneously vary two or more independent variables, such as drug treatment and cell line. Factorial designs often provide additional information at little extra cost. Experiments need to be carefully planned to avoid bias, be powerful yet simple, provide for a valid statistical analysis and, in some cases, have a wide range of applicability. Virtually all experiments need some sort of statistical analysis in order to take account of biological variation among the experimental subjects. Parametric methods using the t test or analysis of variance are usually more powerful than non-parametric methods, provided the underlying assumptions of normality of the residuals and equal variances are approximately valid. The statistical analyses of data from a completely randomised design, and from a randomised-block design are demonstrated in Appendices 1 and 2, and methods of determining sample size are discussed in Appendix 3. Appendix 4 gives a checklist for authors submitting papers to ATLA.
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