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ERA vs ECOLOGICAL RESEARCH
The importance
of
a good problem formulation
Dr Joe Smith
DIVERSE CROPS / TRAITS
Drought tolerance Insect resistance
Salt tolerance Water use efficiency
Altered starch Nitrogen use efficiency
Enhanced nutrition Disease resistance
Altered oil content Fungal resistance
Improved fibre Sugar content
Herbicide tolerance
OUTLINE
ERA Vs ecological research
Problem formulation What is it?
Key factors
Role in risk assessment process
What data do we really need to know? Sufficient, relevant and credible
ERA ≠ ECOLOGICAL RESEARCH
Both address problems and test hypotheses
BUT
Different problem selection
Different types of hypotheses
Different testing of hypotheses
Confusion ineffective ERA & inadequate research
[Raybould 2008, 2010]
≠
ERA ≠ ECOLOGICAL RESEARCH
Research
• Problem - objective (from analysis of prior problems)
• Hypotheses - interesting (make precise predictions)
• Testing - aims to falsify hypothesis (corroborated by presence of
phenomena in field studies)
ERA
• Problem - subjective (from definitions of harm)
• Hypotheses - useful (predict no harm)
• Testing - aims to falsify hypothesis (corroborated by absence of phenomena in lab studies)
[Raybould 2008, 2010]
Essential to have clearly defined problem so that risk assessors can
conclude with some certainty that particular harms will not eventuate
PROBLEM FORMULATION WHAT IS IT?
‘…the first step in ERA where policy goals, scope, assessment endpoints, and methodology are distilled to an explicitly stated problem and approach for analysis’
• Improved consistency and focus of ERAs
• Enhances relevance and utility for regulatory decision-making
[Wolt et al, 2010]
PROBLEM FORMULATION KEY FACTORS
Legislation / regulations
Risk analysis process
Risk context
Protection goals – specific harms
Identify risks that genuinely need further analysis
Remove hypothetical or negligible risks
‘The formulation of a problem is often more important than its solution’ (Albert Einstein)
LEGISLATION AND REGULATIONS
The government mandate
Reflects community values, expectations
Responsibilities for decisions
Scope, definitions
High level regulatory criteria
RISK ANALYSIS PROCESS INCORPORATING PROBLEM FORMULATION
[Wolt et al, 2010]
RISK CONTEXT
Critical factor in framing the risk assessment, problem formulation and determining what we need to know
• Canola parent (B napus) – exotic, annual/biennial, natural toxicants, weed in agricultural but not undisturbed habitats
• Activities – as for commercial non-GM canola; widespread cultivation for oil, meal production
• Traits - herbicide tolerance
increased competitiveness in presence of herbicides
• Receiving environment – biotic and abiotic factors,
agricultural practices, related plants, related proteins
• Previous releases – field trials, commercial, overseas
CONTEXT FOR HT CANOLA [Commercial release]
Source: OGTR
• Expect few identified risks because of proposed limits and controls
• Measures to limit and control release:
Separate trial sites – pollen traps or isolation zones
Harvest trial plants separately
Clean equipment, destroy unused plant material
Monitor site, destroy volunteer plants
Regulator’s Guidelines for transport
No use for human or animal feed
CONTEXT FOR FIELD TRIALS
Source: OGTR
• Define assessment endpoints
• Identify characteristics of GM plants with potential to cause adverse effects
• Postulate exposure pathways for these adverse effects to occur
• Outline specific risk hypotheses to guide data generation and evaluation
• Develop conceptual model (pathways to harm) and analysis plan
FORMULATING THE
PROBLEM
RISK CONTEXT
Activities with
GM crop
Harm to people
or environment
Risk Scenario = plausible pathway to harm
Source: OGTR
EXAMPLE FOR COTTON
ACTIVITY GM cotton containing Bt gene
HARM Reduced plant biodiversity in protected area
Risk Scenario = plausible pathway to harm
Loss of GM seed during transport
Establishment of GM cotton near native cotton
Gene flow from GM to native cotton
Increased weediness of native cotton
Source: OGTR
DATA QUALITY, SUFFICIENCY & RELEVANCE
What is the quality of evidence ?
Is the data available relevant and sufficient?
What uncertainty is there with the estimate of risk ?
Is uncertainty relevant or important ?
CONCLUSIONS
• Regulatory risk analysis is not research – it is a structured mechanism for making effective and timely decisions using available information and taking account of uncertainty
• Problem formulation is critical in ensuring the ERA considers only
relevant and credible risks and is useful for decision-making
• Potential harms, assessment endpoints and credible pathways to the harms need to be clearly identified at the beginning of the ERA
• Problem formulation helps ensure that data used in ERA of GM crops is relevant to the questions that need to be answered
• Credibility, quality and relevance of data is essential
ACKNOWLEDGEMENT
The views expressed in this presentation are my personal views alone and not those of any government agency. They are derived in large part from my experiences as Australia’s Gene Technology Regulator and I remain indebted to the outstanding staff of the Office of the Gene Technology Regulator.