Equivalence criteria for the safety evaluation of a genetically modified crop: a statistical perspective

Abstract

SUMMARYSafety evaluation of a genetically modified (GM) crop is accomplished by establishing its substantial equivalence to non-GM reference crops with a history of safe use. Testing hypotheses of equivalence rather than difference is the appropriate statistical approach. A necessary first step in this regard is to specify a reasonable equivalence criterion that includes a measure for discrepancy between the GM and reference crops as well as a regulatory threshold. The present work explored several equivalence criteria and discussed their pros and cons. Each criterion addresses one of three ordered classes of equivalence: super, conditional and marginal equivalence. Their implications were investigated over an array of parameter values estimated from a real-world dataset. Marginal equivalence was identified as adhering most closely to the concept of substantial equivalence. Because conditional equivalence logically implies marginal equivalence and is practically quantifiable from current field designs, the present work recommends conditional equivalence criteria while encouraging producers to improve their design to enable testing marginal equivalence in the future. Contrary to concerns of the ag-biotech industry, empirical evidence from recent publications indicates that a linear mixed model currently implemented by the European Food Safety Authority is adequate for assessing equivalence despite its lack of genotype-by-environment interaction terms.