RESPONSES

SCIENCE-BASED RISK ANALYSIS

Risk analysis is concerned with how to evaluate, contain or avoid negative impacts resulting from the uncertain behaviour of GM products and processes. To be effective, such assessments need to address all costs-and-benefits, and not be restricted to financial expenditures and profits (Young 2004). It needs to address direct and indirect costs-and-benefits, as well as opportunity costs, such as the impact on environmental goods-and-services as well as on agricultural and social systems. Field trials and how crops behave in conditions similar to those following actual release are a critical step in the assessment process, allowing product developers to address problems arising. They play an important role in identifying risks and creating an opportunity for mitigation and adaptation prior to full release.

However, the standardized approach to risk assessment does not allow for such levels of complexity. Most national risk analysis frameworks focus on risk-benefit assessments that are derived from economic cost-benefit type analysis. In general, they adopt narrow technical approaches, which focus on the characteristics of the host organism and the resulting GMO, the expression and properties of the gene product and the biophysical features of the recipient environment (Mohamed-Katerere 2003). These approaches and their general principles have been developed over several decades in response to technological development in the chemical and pharmaceutical industries. These standardized approaches are particularly attractive to companies and governments as they are simplified and avoid the costs of case-by-case analysis.

Two factors underlie the analysis of risk (Young 2004):

  • The magnitude of each potential harm or benefit that might occur; and
  • The likelihood of its occurrence.

Magnitude is particularly important from a human and environmental perspective; certain kinds of changes, such as biodiversity loss, may be irreversible. Magnitude is difficult to ascertain where there is insufficient experience with a product or activity. Likelihood is based on comparison with similar situations in the past.

SUBSTANTIAL EQUIVALENCE AND FAMILIARITY

In the area of GM crops, many national assessment systems are based on the concepts of “substantial equivalence” and “familiarity” to determine the likelihood of potential harm (Scoones 2002) and to decide on further product testing and development as well as commercial release. In general, it neglects the socioeconomic aspects.

The concept of familiarity has been used in the chemical industry to determine safety levels on the assumption that closely related chemicals will behave in the same way. This approach is now used in GM risk assessment. Such models have a high level of appeal because they do not require regulators to deal with complex and case-specific factors. This framework neglects the issue of magnitude and rare but significant impacts. It may not be as well suited to LMO as these can behave in unpredictable ways.

Substantive equivalence between organisms is used as an indication of how they will behave. The concept was originally developed as a way for determining food safety (Scoones 2002). If a new GM product is substantially equivalent in chemical composition to its natural antecedent then it is assumed to be safe. This approach neglects the uncertainties around the actual modification of DNA.