Toxicity testing of human assisted reproduction devices using the mouse embryo assay.

Systems to assess the toxicity of materials used in human assisted reproduction currently lack efficiency and/or sufficient discriminatory power. The development of 1-cell CBA/B6 F1 hybrid mouse embryos to blastocysts, expressed as blastocyst rate (BR), is used to measure toxicity. The embryos were divided into control and test groups, and were exposed to either control medium or to a potentially toxic test medium. Inferences on toxicity were based on differences in BR between the two groups. The mouse embryo assay followed a stratified (mouse), randomized (embryo), and balanced (equal number of embryos per group and per mouse) design. The number of embryos needed was calculated using power analysis. The basal BR of the hybrid strain was determined in a historical population. Sixty-nine mouse embryos per group were required to detect toxic materials with sufficient sensitivity and to account for the considerable inter-mouse variation in blastocyst development. Fifty-two samples, divided over batches of seven different products were tested before use in the study IVF centre and five of these were found to be toxic. This test system, presented as the Nijmegen mouse embryo assay (NMEA), can be used to detect embryo-toxic materials in daily IVF practice, and this report may provide a starting point for standardization.

Sample size calculations for a split-cluster, beta-binomial design in the assessment of toxicity.

Mouse embryo assays are recommended to test materials used for in vitro fertilization for toxicity. In such assays, a number of embryos is divided in a control group, which is exposed to a neutral medium, and a test group, which is exposed to a potentially toxic medium. Inferences on toxicity are based on observed differences in successful embryo development between the two groups. However, mouse embryo assays tend to lack power due to small group sizes. This paper focuses on the sample size calculations for one such assay, the Nijmegen mouse embryo assay (NMEA), in order to obtain an efficient and statistically validated design. The NMEA follows a stratified (mouse), randomized (embryo), balanced design (also known as a split-cluster design). We adopted a beta-binomial approach and obtained a closed sample size formula based on an estimator for the within-cluster variance. Our approach assumes that the average success rate of the mice and the variance thereof, which are breed characteristics that can be easily estimated from historical data, are known. To evaluate the performance of the sample size formula, a simulation study was undertaken which suggested that the predicted sample size was quite accurate. We confirmed that incorporating the a priori knowledge and exploiting the intra-cluster correlations enable a smaller sample size. Also, we explored some departures from the beta-binomial assumption. First, departures from the compound beta-binomial distribution to an arbitrary compound binomial distribution lead to the same formulas, as long as some general assumptions hold. Second, our sample size formula compares to the one derived from a linear mixed model for continuous outcomes in case the compound (beta-)binomial estimator is used for the within-cluster variance.