presentation 3 biography
TRANSCRIPT
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Presentation 3
Applying mathematical modelling to crop protection development
Dr Kim Travis; Syngenta
By the late 1980s, mathematical modelling was used internally by the computational chemistry and chemical
engineering groups, and had recently started to be used by regulatory authorities in the USA, but experimental
approaches dominated. Whilst the discovery and development of a new crop protection product is still
dominated by empirical approaches, the use of mathematical modelling for internal decision-making has
considerably increased. The use of modelling to support regulatory decision-making has changed relatively
little in the USA, but in the EU has been totally transformed. Loud voices calling for model validation have
gradually been replaced by the recognition of the advantages of a model-based approach in the regulatory
process. In some domains the process has even gone too far, such that data is not believed if seems to be out
of line with the models! There has been most progress in modelling of the environmental fate and risk
assessment of chemicals, whilst change in mammalian toxicology and food residue assessment has been
much slower. I will try to identify the reasons why the acceptance and adoption of mathematical modelling has
varied so much in different scientific domains, internally vs externally, and between different regions.
Biography
Kim Travis is a biologist by training, who has a long standing interest in the modelling of biological systems. He
was employed in a Syngenta legacy company as a mathematical modeller in 1988. Since then he has worked
on all aspects of the safety of crop protection products, and has worked on projects ranging from new
chemical discovery through to supporting products that have been on the market for over 50 years. Kim is
currently a Syngenta Fellow, based at the Jealott’s Hill site in Berkshire. Syngenta is the world’s largest crop
protection company.
Kim Travis Sept 2016
Applying mathematical modelling to crop protection development
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Outline
● Introduction● Uses of modelling within Syngenta● Uses of modelling in pesticide regulation● What enables the use of modelling in regulation?● Opportunities
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Crop protection
● This means herbicides, fungicides and insecticides, i.e. pesticides- Protect yields, keep food affordable and meet population growth food
security challenge● Much as for traditional pharmaceuticals
- Small biologically-active molecules- Large discovery and screening effort- Many years and a huge amount of money from discovery to sales- Very strict regulatory process
● Unlike pharmaceuticals- We do far more ecological/environmental safety work- We don’t generally test our molecules in humans
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Why are models used? Because they are useful!
Mathematical models express our ideas of how the world works in terms of equations
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Modelling can save time, reduce risk and save money
…and deliver 3Rs benefits!
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Modelling is everywhere in Syngenta
Model organisms Model environments
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Animal studies and mathematical models are all models- we shouldn’t be thinking of them as fundamentally different
The issue with modelling is often not so much not validation, but acceptance
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Outline
● Introduction● Uses of modelling within Syngenta
● Uses of modelling in pesticide regulation● What enables the use of modelling in regulation?● Opportunities
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Experimentation Modelling
Insight
Foresight
virtuous circle
better understanding
prediction
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Predictive toxicology
Existing knowledge in silico in vitro in vivo
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• Acute toxicity (rats)• General repeat dose toxicity (rats, mice, dogs)• Genetic toxicity (in vitro, in vivo in rats and mice)• Carcinogenicity (rats, mice)• Development toxicity (rats, rabbits)• Reproductive toxicity over generations (rats)• Absorption, Distribution, Metabolism & Excretion (ADME)
Pesticide regulatory toxicology studies
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Outline
● Introduction● Uses of modelling within Syngenta● Uses of modelling in pesticide regulation
● What enables the use of modelling in regulation?● Opportunities
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Pesticide regulation
● Is it safe?- convince yourself- convince regulators too!
● Regulatory approval is a pre-requisite for product sales
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Safety to manSafety to the
environment
Mammalian
toxicologyChemical fate
and exposure Ecotoxicology
The use of models in pesticide regulation
Niche uses Dominant role Increasing use
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Role of environmental fate modelling in pesticide regulation in the EU
● Major role envisaged when EU rules were drafted in early ‘90s- For a new pesticide, environmental contamination could take years
to appear, so only models could address the need to ensure it could be protected against
- Then had to work out how to achieve the regulatory objectives with modelling FOCUS
• a forum for regulators, government institutes and industry to work out the details (mid ‘90s to mid ’00s)
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Rain
Soil Properties
Leaching
Runoff
EvaporationTranspiration
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EU pesticide leaching assessment- the original FOCUS standard scenarios
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Standardised• Weather• Soil• Cropping
So regulatory evaluation can focus on pesticide properties• Use pattern• Soil absorption• Metabolism• ……
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- maximises value of expensive studies- fits studies into a risk assessment- put study results into a real-world context
Use of models to aid study interpretation
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Outline
● Introduction● Uses of modelling within Syngenta● Uses of modelling in pesticide regulation● What enables the use of modelling in regulation?
● Opportunities
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What have we learnt?
● Mathematical modelling using standard scenarios can provide a level playing field for chemical regulation
But you also need● Good version control● A home (“institutionalisation”)● Documentation
…Models of ecological population dynamics- because the regulatory goal is to protect populations, not individuals- in crop protection, led to a large degree by my Syngenta colleague
Pernille Thorbek
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● “…the current practice of modelling as published in the scientific literature needs some adjustments before it can be applied to
regulatory risk assessments.”● “To achieve this, modellers will have to follow good modelling practice.
A good start would be to include comprehensive and coherent
model descriptions, as many of the models that were reviewed did not include a full description of model design and input parameters.
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What do we need to base decisions on ecological models?
● CREAM project http://cream-itn.eu/
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THE MODELING CYCLE
Schmolke A, Thorbek P, DeAngelis DL, Grimm V. 2010.
Trends in Ecology and Evolution 25: 479-486
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Verification and sensitivity analysis
● Verification: checking implementation- does the model do what you think it does?
● Sensitivity analysis- what parameters have the greatest influence on the outputs?- are there interactions between parameters?
● For complex models also model exploration: why do the model produce the patterns it does?
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It’s not just about what the modeller needs to do…
Stuff model “customer” needs to do
Stuff to discuss with modeller
Stuff modeller should do
Stuff to ask an independent expert about
Stuff model assessor should do
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Model communication
● Important for acceptance!- Lack of transparency leads to scepticism
● Documentation of model- Experiments should be described so others can repeat them- Same goes for models – but often not the case
From Schmolke et al 2010; TREE 25: 479-486
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Outline
● Introduction● Uses of modelling within Syngenta● Uses of modelling in pesticide regulation● What enables the use of modelling in regulation?● Opportunities
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Lord Kelvin
“I often say that when you can measure what you are speaking about and express it in numbers you know something about it; but when you cannot express it in numbers your knowledge is of a meagre and unsatisfactory kind: it may be the beginning of knowledge but you have scarcely, in your thoughts, advanced to the stage of science, whatever the matter may be.”
We need to quantitatively simulate processes resulting in
toxic outcomes - systems biology models, human disease
models, adverse outcome pathway (AOP) modelling
● From the Descriptive to the Predictive
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chemical properties
in vitro data
in vivo data
Opportunities for prediction (QSARs and structural alerts)
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Toxicologydatasets
Machinelearning
Questions
Models
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Working towards a more collaborative approach
● Pre-competitive data sharing, the power of numbers, 3Rs● Influence of crowdsourcing, social media, open-source
Public domain data & models
Syngenta
data & models
Company Bdata and models
Company A data and models
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Why are models used? Because they are useful!
So make sure your models are useful