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Day 1 Summary
EXPERT WORKSHOP ON PRACTICAL APPLICATIONS OF WGS ON FOOD SAFETY
Game changer?
 Real-time application is key
 Advantage to exchange a common language
 Already existing good epi system and real-time surveillance system –
extremely useful, but are they essential?
 Simple food-testing is available everywhere
 Step-by-step approach can be taken with things that exist
 Political will to improve food safety – useful (in other words, countries that
consider food safety a low priority – a challenge)
Case studies to highlight benefits
 Why WGS is better than traditional methods?
 Simpler*
 More sensitive/precise/specific (inclusion/exclusion of cases in clusters, “matches”)
 Faster (minimize the negative impact)
 Concrete information/evidence for actions, improved confidence
 Handling of WGS data is easier than PFGE*
 Performing is easier*
 Low cost (if high volume)
 Application flexibility
 Why WGS is beneficial for developing countries?
 Easy to implement*
 Helps build confidence of the competent authority at the national level
 Global identification of the problem can help local identification/intervention
Possible pitfalls
 Realistic descriptions of possible pitfall needs to be in the paper
 Essential infrastructure to employ WGS – internet connection/speed
 Are there any prerequisite activities to conduct before employing WGS?
 Acquiring and analyzing exposure data – limiting factor
 Interpretation of the data – bioinformatics capacity development needs
 Challenges in traditional methods remain as challenges in WGS (epi, food investigations, sampling, etc)
 Obvious technological challenges with new methodologies
 Cost (if low volume)
 Trust issue – Is your data credible? What will happen to my data?
 Fears of global data sharing – trade barriers?
 Needs to highlight to educate that earlier intervention is a clear benefit in the long-run, with minimized adverse
health impact, reduced economical impact, fewer lawsuits, less impact overall
 Who will have responsibility for global-level monitoring and action?
 Consideration on different level of development
Data-sharing
 Benefit of global data-sharing – for developing countries?
 Raw data sharing – useful, but “what if”
 Confidentiality issue
 Ownership issue – my isolates, my sequenced data
 Data submitters + Data mediator(s) – blinded way
 Not very simple for WHO to be a “global submitter/mediator – still a need for international
hub
 Possibility with academia/universities as data mediator(s)
 Issues with meta data – what would be “minimum” requirement?
 Global vs local
 “Draft” data sharing possibility – for real-time actions
WGS implementation challenges
 Resources
 Perception of high cost of the new technology
 Still high cost in developing countries
 Parallel with traditional tests – double/triple the costs?
 New methodologies
 Training and trained personnel needed
 Sensitization needs for higher authorities and politicians – why do we need
WGS?
 Global data-sharing: consequences – uncertain - leads ones to keep data
locally
Capacity building
 Basic food safety capacity building still very relevant
 Health surveillance
 Food monitoring
 Foodborne illness investigations
 Food inspection
 Traceability/recall
 Risk analysis
 Trainings vs providing “good practices” + trainings
 Guidance on harmonization
Role of international organizations
 “Convening power”
 Providing fora to discuss global issues – governance issues, legal issues,
confidential issues, IPRs
 “Good practice” guidelines for harmonization
 Validation of the data? Facilitation of sharing data
 Coordination of global cluster investigation?
 Collaboration with major relevant initiatives to facilitate synergies
 Networks: PulseNet international, ICOPHAI (GenomeTrakr partnership) – one health
 Databases (NCBi/ENA/DDJ)
 Consortium: GMI, etc
Considerations
 Multi-agency collaboration – essential (food and health)
 Multi-sectoral collaboration – extremely useful (public, private, academia,
etc)
 With appropriate governmental policies, WGS can help to limit the impact
of outbreaks through faster and more accurately link outbreaks with food
source and help
 increasing food safety and public health,
 minimizing the impact of contaminated food on trade and
 minimizing food waste

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Summary presentation of day one FAO experts workshop on practical applications on Whole Genome Sequencing (WGS) for food safety management

  • 1. Day 1 Summary EXPERT WORKSHOP ON PRACTICAL APPLICATIONS OF WGS ON FOOD SAFETY
  • 2. Game changer?  Real-time application is key  Advantage to exchange a common language  Already existing good epi system and real-time surveillance system – extremely useful, but are they essential?  Simple food-testing is available everywhere  Step-by-step approach can be taken with things that exist  Political will to improve food safety – useful (in other words, countries that consider food safety a low priority – a challenge)
  • 3. Case studies to highlight benefits  Why WGS is better than traditional methods?  Simpler*  More sensitive/precise/specific (inclusion/exclusion of cases in clusters, “matches”)  Faster (minimize the negative impact)  Concrete information/evidence for actions, improved confidence  Handling of WGS data is easier than PFGE*  Performing is easier*  Low cost (if high volume)  Application flexibility  Why WGS is beneficial for developing countries?  Easy to implement*  Helps build confidence of the competent authority at the national level  Global identification of the problem can help local identification/intervention
  • 4. Possible pitfalls  Realistic descriptions of possible pitfall needs to be in the paper  Essential infrastructure to employ WGS – internet connection/speed  Are there any prerequisite activities to conduct before employing WGS?  Acquiring and analyzing exposure data – limiting factor  Interpretation of the data – bioinformatics capacity development needs  Challenges in traditional methods remain as challenges in WGS (epi, food investigations, sampling, etc)  Obvious technological challenges with new methodologies  Cost (if low volume)  Trust issue – Is your data credible? What will happen to my data?  Fears of global data sharing – trade barriers?  Needs to highlight to educate that earlier intervention is a clear benefit in the long-run, with minimized adverse health impact, reduced economical impact, fewer lawsuits, less impact overall  Who will have responsibility for global-level monitoring and action?  Consideration on different level of development
  • 5. Data-sharing  Benefit of global data-sharing – for developing countries?  Raw data sharing – useful, but “what if”  Confidentiality issue  Ownership issue – my isolates, my sequenced data  Data submitters + Data mediator(s) – blinded way  Not very simple for WHO to be a “global submitter/mediator – still a need for international hub  Possibility with academia/universities as data mediator(s)  Issues with meta data – what would be “minimum” requirement?  Global vs local  “Draft” data sharing possibility – for real-time actions
  • 6. WGS implementation challenges  Resources  Perception of high cost of the new technology  Still high cost in developing countries  Parallel with traditional tests – double/triple the costs?  New methodologies  Training and trained personnel needed  Sensitization needs for higher authorities and politicians – why do we need WGS?  Global data-sharing: consequences – uncertain - leads ones to keep data locally
  • 7. Capacity building  Basic food safety capacity building still very relevant  Health surveillance  Food monitoring  Foodborne illness investigations  Food inspection  Traceability/recall  Risk analysis  Trainings vs providing “good practices” + trainings  Guidance on harmonization
  • 8. Role of international organizations  “Convening power”  Providing fora to discuss global issues – governance issues, legal issues, confidential issues, IPRs  “Good practice” guidelines for harmonization  Validation of the data? Facilitation of sharing data  Coordination of global cluster investigation?  Collaboration with major relevant initiatives to facilitate synergies  Networks: PulseNet international, ICOPHAI (GenomeTrakr partnership) – one health  Databases (NCBi/ENA/DDJ)  Consortium: GMI, etc
  • 9. Considerations  Multi-agency collaboration – essential (food and health)  Multi-sectoral collaboration – extremely useful (public, private, academia, etc)  With appropriate governmental policies, WGS can help to limit the impact of outbreaks through faster and more accurately link outbreaks with food source and help  increasing food safety and public health,  minimizing the impact of contaminated food on trade and  minimizing food waste