A statistical assessment of differences and equivalences between genetically modified and reference plant varieties

Abstract

BackgroundSafety assessment of genetically modified organisms is currently often performed by comparative evaluation. However, natural variation of plant characteristics between commercial varieties is usually not considered explicitly in the statistical computations underlying the assessment.ResultsStatistical methods are described for the assessment of the difference between a genetically modified (GM) plant variety and a conventional non-GM counterpart, and for the assessment of the equivalence between the GM variety and a group of reference plant varieties which have a history of safe use. It is proposed to present the results of both difference and equivalence testing for all relevant plant characteristics simultaneously in one or a few graphs, as an aid for further interpretation in safety assessment. A procedure is suggested to derive equivalence limits from the observed results for the reference plant varieties using a specific implementation of the linear mixed model. Three different equivalence tests are defined to classify any result in one of four equivalence classes. The performance of the proposed methods is investigated by a simulation study, and the methods are illustrated on compositional data from a field study on maize grain.ConclusionsA clear distinction of practical relevance is shown between difference and equivalence testing. The proposed tests are shown to have appropriate performance characteristics by simulation, and the proposed simultaneous graphical representation of results was found to be helpful for the interpretation of results from a practical field trial data set.

Guidance for risk assessment of food and feed from genetically modified plants

“…Detailed guidance on the experimental design for the safety evaluation of GM plants is provided in the EFSA guidance on "Statistical considerations for the safety evaluation of GMOs" (EFSA, 2010b;van der Voet et al, 2011).…”

Characterisation of immune responses in healthy foals when a multivalent vaccine protocol was initiated at age 90 or 180 days

“…Bioequivalence testing was also conducted at the end of the study, that is at 254 days after initiation of the study. Following Van der Hoat [14] and Tempelman [15]. Average treatment bioequivalence for each response variable was declared at a 5% level of significance if the 90% confidence interval on the mean difference (expressed in the transformed scale) laid within ± equivalence limits specified at 5 and 10 units relative to the control and in the direction of the treatment mean.…”

7.3 Process Characterization for Upstream and Downstream Process Development

“…A common approach used is univariate analysis, where each parameter at small scale is compared to the corresponding value at manufacturing scale using statistical measures or by demonstrating equivalency of the parameters means at the different scales [29]. However, with increasingly complex multidimensional data sets being generated from cell culture and purification processes, it becomes difficult and inefficient to use a univariate approach.…”