A semi-quantitative approach to GMO risk-benefit analysis

被引:11
|
作者
Morris, E. Jane [1 ]
机构
[1] African Ctr Gene Technol, ZA-0040 Lynnwood Ridge, South Africa
关键词
Genetically modified organisms; Risk assessment; Risk-benefit; Regulation; RAPID IMPACT ASSESSMENT; ASSESSMENT MATRIX RIAM; RELEASE; CROPS; RICE; ENVIRONMENT;
D O I
10.1007/s11248-010-9480-8
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:1055 / 1071
页数:17
相关论文
共 50 条
  • [1] A semi-quantitative approach to GMO risk-benefit analysis
    E. Jane Morris
    Transgenic Research, 2011, 20 : 1055 - 1071
  • [2] A semi-quantitative approach to risk analysis, as an alternative to QRAs
    Aven, Terje
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2008, 93 (06) : 790 - 797
  • [3] Quantitative risk-benefit analysis of natalizumab
    Thompson, J. P.
    Noyes, K.
    Dorsey, E. R.
    Schwid, S. R.
    Holloway, R. G.
    NEUROLOGY, 2008, 71 (05) : 357 - 364
  • [4] QUANTITATIVE RISK-BENEFIT ANALYSIS OF NATALIZUMAB
    Steiner, Israel
    NEUROLOGY, 2009, 72 (20) : 1791 - 1791
  • [5] Semi-Quantitative Benefit-Risk Assessment for Dengvaxia
    Marcelon, Lydie F.
    Cohen, Carine H.
    Khromava, Alena
    Ochiai, Leon R.
    Wartel, Anh T.
    Gailhardou, Sophia
    PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2016, 25 : 289 - 290
  • [6] Risk assessment in genetics: A semi-quantitative approach
    Glasspool, DW
    Fox, J
    Coulson, AS
    Emery, J
    MEDINFO 2001: PROCEEDINGS OF THE 10TH WORLD CONGRESS ON MEDICAL INFORMATICS, PTS 1 AND 2, 2001, 84 : 459 - 463
  • [7] Assessing a structured, quantitative health outcomes approach to drug risk-benefit analysis
    Garrison, Louis P., Jr.
    Towse, Adrian
    Bresnahan, Brian W.
    HEALTH AFFAIRS, 2007, 26 (03) : 684 - 695
  • [8] Incorporating assumption deviation risk in quantitative risk assessments: A semi-quantitative approach
    Khorsandi, Jahon
    Aven, Terje
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2017, 163 : 22 - 32
  • [9] Risk-benefit analysis
    Mossman, KL
    HEALTH PHYSICS, 2002, 82 (05): : 750 - 750
  • [10] Risk-benefit analysis
    Wilson, R.
    Crouch, E.A.C.
    Physics Today, 2002, 55 (10)