Policy-led comparative environmental risk assessment of genetically modified crops: Testing for increased risk rather than profiling phenotypes leads to predictable and transparent decision-making

Alan Raybould, Phil Macdonald

Research output: Contribution to journalArticlepeer-review

Abstract

We describe two contrasting methods of comparative environmental risk assessment for genetically modified (GM) crops. Both are science-based, in the sense that they use science to help make decisions, but they differ in the relationship between science and policy. Policy-led comparative risk assessment begins by defining what would be regarded as unacceptable changes when the use a particular GM crop replaces an accepted use of another crop. Hypotheses that these changes will not occur are tested using existing or new data, and corroboration or falsification of the hypotheses is used to inform decision-making. Science-led comparative risk assessment, on the other hand, tends to test null hypotheses of no difference between a GM crop and a comparator. The variables that are compared may have little or no relevance to any previously stated policy objective and hence decision-making tends to be ad hoc in response to possibly spurious statistical significance. We argue that policy-led comparative risk assessment is the far more effective method. With this in mind, we caution that phenotypic profiling of GM crops, particularly with omics methods, is potentially detrimental to risk assessment.
Original languageEnglish
Article number43
Pages (from-to)1-7
Number of pages7
JournalFrontiers in Bioengineering and Biotechnology
Volume6
DOIs
Publication statusPublished - 10 Apr 2018

Keywords

  • risk assessment
  • genetically modified crops
  • regulatory policy
  • problem formulation
  • profiling
  • hypothesis testing

Fingerprint

Dive into the research topics of 'Policy-led comparative environmental risk assessment of genetically modified crops: Testing for increased risk rather than profiling phenotypes leads to predictable and transparent decision-making'. Together they form a unique fingerprint.

Cite this