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Development of an Institutional Knowledge-base at FDA’s Center
for Food Safety and Applied Nutrition
Kirk B. Arvidson1, Annette McCarthy1, Chihae Yang2, Dimitar Hristozov1
1)U.S. Food and Drug Administration (FDA)Center for Food Safety and Applied Nutrition (CFSAN)
Office of Food Additive Safety (OFAS)2) The Ohio State University, Columbus, Ohio
Outline
• Introduction
• CERES workflow
• Database scheme
• Query Results
• QSAR models
• Q&A
Office Of Food Additive Safety (OFAS)
• OFAS is a program office within CFSAN– Ensure the safety of food additives and
packaging in U.S.• Evaluate safety information in industry submissions
for various categories of food ingredients– Direct food additives (e.g., high intensity sweeteners)– Biotech foods (e.g., herbicide-ready soybeans)– Generally Recognized as Safe (GRAS – phosphoric acid)– Food contact substances (e.g., plastic bottles, sanitizers)
Pre- and Post-market Evaluations• Shortfall of current processes
– Rely on institutional knowledge– Data is sequestered in multiple small databases – Accessing/locating data can be difficult and time consuming– Difficult to keep data up to date-time and resource intensive – No systematic method to bring together disparate tox. data on a
compound or its structural and biological analogues
• Current needs– A centralized knowledgebase accessible from desktop computer– Real time access to data-both internal and external sources– Relate new and existing data in new ways– Leveraging knowledge more efficiently– Make sound decisions faster
Chemical Evaluation and Risk Estimation System (CERES)
• Food additives knowledge-base– Captures institutional knowledge– Chemical centric– Structured data/controlled vocabulary
• Desktop access to:– Internal and external chemical and toxicity data– Structure analog searching and data retrieval– QSAR Models– Threshold of Toxicological Concern evaluations
CERES Workflow
O
O
HN
NH2
OH
O
O
Decision Support for Safety Assessment
Pre-market Safety Decisions
Post-market Safety Decisions
Post-market Review Portal
Pre-market Review Portal
Submission DataLiterature Data
Computational Toxicology•Read-across•Rule-base•Mode of action models•Threshold of toxicological
concern (TTC)
Safety Alert
Knowledgebase
Results Set
O
O
HN
NH2
OH
O
O
O
O
HN
NH2
OH
O
O
Decision Support for Safety Assessment
Pre-market Safety Decisions
Post-market Safety Decisions
Post-market Review Portal
Pre-market Review Portal
Submission DataLiterature Data
Computational Toxicology•Read-across•Rule-base•Mode of action models•Threshold of toxicological
concern (TTC)
Safety Alert
Knowledgebase
Results Set
O
O
HN
NH2
OH
O
O
O
O
HN
NH2
OH
O
O
Decision Support for Safety Assessment
Pre-market Safety Decisions
Post-market Safety Decisions
Post-market Review Portal
Pre-market Review Portal
Submission DataLiterature Data
Computational Toxicology•Read-across•Rule-base•Mode of action models•Threshold of toxicological
concern (TTC)
Safety Alert
Knowledgebase
Results Set
O
O
HN
NH2
OH
O
O
Knowledgebase
Results Set
O
O
HN
NH2
OH
O
O
Simplified Database Scheme
Query Page
Query Results: Regulatory Summary
Query Results: Study Summary
Prediction Models
Weight of evidence and mode of action models
MoA classes
Aldehydes PhenolsAromatic Amines Alkyl halidesGlobal
Not likely mutagenic
Categories
Likely mutagenic
........
Alerts
NH2
OH
NH 2
OH
0.8860.621
0.7230.723
Weight of evidence averagingWeight of evidence averaging
NH2
OH
0.588
Enhance Pre-, Post-market Evaluation of Food IngredientsThrough Threshold of Toxicological Concern Approach
TTCvalues
Repro-GreenDev.-BlueCarc.-Red????-Grey
OO OO
TTC Values
DatabaseDatabase
StructureCategories
Enhance Pre-, Post-market Evaluation of Food Ingredients
Repro-GreenDev.-BlueCarc.-Red????-Grey
StructureCategories
Regulatory ActionAdditional Data Needs
O
OHExposure
TTCvalues
Query
Chemical C
lasses
Chemical C
lasses
conc
ern
fact
orco
ncer
n fa
ctor
Red: high concern Yellow: intermediateGreen: low concern
threshold
exposure factor concern
Profiling Toxicological Concerns With Chemical and Biological Classes
Biological endpointsBiological endpoints
Computational Toxicology Paradigm
ToxCastTM and Tox21
• Molecular signatures – biology/chemistry
• High Throughput Screening assays (>500)– cell-based assays– cell-free target-based assays
• Leverage legacy toxicity data
BJ-range-ViabilityJurkat-range-Viability
SKNSH-range-ViabilityN2A-range-CaspaseN2A-range-Viability
Hep-G2-range-ViabilityMRC5-range-ViabilityHUVEC-range-Viability
Mesench-range-ViabilityBJ-range-CaspaseSHSY5-range-Caspase
Hek293-range-CaspaseHek-293-range-ViabilityRenal-range-Viability
SH5Y-range-Viability3T3-range-ViabilityH4IIe-range-Viability
3T3-range-CaspaseJNK.Alpha.Screen.-.rangeH4IIe-range-Caspase
HepG2-range-CaspaseHUVEC-range-CaspaseIkB.signalling.-.range
Jurkat-range-Caspase
Rat
Rat
(F)
Rod
ent
ivtC
A
Mou
se
Mou
se(M
)
Mou
se(F
)
invi
voM
N
TA
100
TA
1535
TA
1537
MM
ut
Rat
(M)
Sal
mon
ella
TA
98
toxicity
bioa
ssay
s
Navigation through chemical classes Red: high corr.; Blue: low corr.
Conclusion• CERES
– Improve Pre- and Post-Market Review• Consolidates information on chemical structure, physical
properties and toxicity data to allow for more robust safety analysis
• Semi-automated monitoring of new safety data relative to authorized chemicals through the use of computational toxicology and TTC
– Relate new and existing data in new ways• Seek biologically meaningful analogs to fill the data gaps
found in many food ingredients and food contact substances• Provide molecular level mechanistic insights that eventually
help us understand human effects• Metabolism knowledge will also be incorporated.
