Transgenic Research

, Volume 20, Issue 5, pp 1055–1071 | Cite as

A semi-quantitative approach to GMO risk-benefit analysis

Original Paper

Abstract

In many countries there are increasing calls for the benefits of genetically modified organisms (GMOs) to be considered as well as the risks, and for a risk-benefit analysis to form an integral part of GMO regulatory frameworks. This trend represents a shift away from the strict emphasis on risks, which is encapsulated in the Precautionary Principle that forms the basis for the Cartagena Protocol on Biosafety, and which is reflected in the national legislation of many countries. The introduction of risk-benefit analysis of GMOs would be facilitated if clear methodologies were available to support the analysis. Up to now, methodologies for risk-benefit analysis that would be applicable to the introduction of GMOs have not been well defined. This paper describes a relatively simple semi-quantitative methodology that could be easily applied as a decision support tool, giving particular consideration to the needs of regulators in developing countries where there are limited resources and experience. The application of the methodology is demonstrated using the release of an insect resistant maize variety in South Africa as a case study. The applicability of the method in the South African regulatory system is also discussed, as an example of what might be involved in introducing changes into an existing regulatory process.

Keywords

Genetically modified organisms Risk assessment Risk-benefit Regulation 

Abbreviations

GMO

Genetically modified organism.

CPB

Cartagena protocol on biosafety

UNCED

United Nations conference on environment and development

PP

Precautionary principle

Bt

Bacillus thuringiensis

EFSA

European food science authority

RIAM

Rapid impact assessment matrix

EIA

Environmental impact assessment

SEA

Strategic environmental assessment

RBS

Risk-benefit score

AS

Agriculture score

FS

Food score

ES

Environment score

HS

Health score

SS

Socio-economic score

P

Probability or likelihood

NEMBA

National environmental management biodiversity act

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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.African Centre for Gene TechnologiesLynnwood RidgeSouth Africa

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