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RELIABILITY OF SAR PREDICTIONS
FOR TTC RISK ASSESSMENT OF NEW
INGREDIENTS
EMGS RISK ASSESSMENT SIG – TUESDAY 24TH SEPT 2013
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DIANA SUAREZ-RODRIGUEZ, PAUL FOWLER AND ANDREW SCOTT Safety & Environmental Assurance Centre
OVERVIEW
Thresholds of Toxicological Concern – their development and use
Role of in silico prediction models
Summary and Conclusions
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WHAT IS THE THRESHOLD OF TOXICOLOGICAL CONCERN (TTC)?
A “pragmatic” risk assessment tool based on the principle of establishing human exposure threshold values below which there is no appreciable risk to human health for a chemical where specific toxicity data may be limited
Originally derived for food contact materials (Frawley 1967)
Cramer, Ford and Hall (1978) developed a decision tree that classifies chemicals on the basis of their chemical properties - Cramer Rules
Three classes: Class I - Low concern chemicals
Class II - Substances less innocuous than Class I, but don’t
contain structural features suggestive of toxicity
Class III - High concern chemicals
Bar Chart
Binned log(NOEL) (1)
Class III
Class II
Class I
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EXPOSURE-DRIVEN RISK ASSESSMENT AND USE OF THE TTC
For food additives, a Threshold of Regulation was derived (1995) - 1.5mg/person/day provided there are no structural alerts for genotoxicity/carcinogenicity
Munro (1996) developed generic thresholds for non-cancer endpoints using a data set of 613 compounds and their related systemic exposure data
Cramer Class 5th Percentile of the NOEL Human exposure threshold
(mg/person/day)
I 1800
II 540
III 90
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CURRENT USE OF THE TTC
Threshold of regulation adopted by FDA on food contaminants (food contact materials)
The TTC approach can be applied to low concentrations in food of chemicals with insufficient toxicity data – Adopted by JECFA on flavouring substances
TTC being investigated for cosmetics ingredients (Blackburn et al 2007, Kroes et al 2007)
Drivers:
Exposure-based risk assessment
Chemicals with insufficient data
Unable to carry out in vivo testing
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TTC DECISION TREE - COSMETICS
Decision tree taken from Kroes et al, 2007, Food Chem. Toxicol., 45, 2533-2562
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EFSA 2012 & SCCS/SCHER/SCENIHR 2012
Removal of the Threshold of Regulation (1.5 mg/person/day)
Re evaluation of Cramer class 2
EFSA (2012). Available from: http://www.efsa.europa.eu/en/efsajournal/pub/2750.htm
SCCS/SCHER/SCENIHR (2012). Available from: http://ec.europa.eu/health/scientific_committees/consumer_safety/docs/sccs_o_092.pdf
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Expressed in terms of kg bw/day
ASSESSMENT OF IN SILICO TOOLS
TTC approach relies on in silico structural alerts to identify genotoxic or carcinogenic potential of an unknown material
In general, in silico tools such as Derek are known to perform well for mutagenicity
No guidance provided by EFSA or SCCS/SCHER/SCENIHR on what approach should be adopted to determine structural alerts
This study aimed to assess the utility of a suite of in silico prediction models as predictive tools for genotoxicity and carcinogenicity using two data sets containing Ames, in vivo MN and CARC data
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ASSESSMENT OF IN SILICO TOOLS
A data set was compiled from publicly available (ISS) and proprietary data sets (Leadscope Enterprise)
A total of 399 compounds with data across the three endpoints
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ISS DATA SET http://www.iss.it
TD50
SMILES
Ames
CARC
Overal l call
214 cpds
in vivo MN
ILSI DATA SET (FDA data extracted
from Leadscope)
TD50
Ames
CARC
Overall call
381 cpds
in vivo MN
SMILES
COMBINED ISS + ILSI
TD50
Ames
CARC
Overall call
399 cpds
in vivo MN
SMILES
GENOTOXICITY DATA SET: DETAILS
Endpoint Positives Negatives Equivocal Inconclusive
Carcinogenicity 265 134
Mutagenicity 160 238 1
in vivo MN 151 241 2 5
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Carcinogens Non-carcinogens
48% are +ve in the Ames 75% are –ve in the Ames
44% are +ve in the in vivo MN 72% are –ve in the in vivo MN
56% +ve in either the Ames or in vivo MN
IN SILICO PREDICTIVE TOOLS
TOXTREE version 2.5.4
DEREK NEXUS version 2.0.3
OECD (Q)SAR TOOLBOX version 3
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IN SILICO PERFORMANCE - TOXTREE
Carcinogenicity and mutagenicity rulebase
A decision tree for estimating carcinogenicity and mutagenicity, based on the rules published in the document: “The Benigni / Bossa rulebase for mutagenicity and carcinogenicity – a module of Toxtree”, by R. Benigni, C. Bossa, N. Jeliazkova, T. Netzeva, and A. Worth. European Commission Report EUR 23241 EN
TOXTREE EXPERIMENTAL CARCINOGENICITY
Positive Negative Total
Positive 169 95 264* Sensitivity = 64%
Negative 46 88 134 Specificity = 66%
*1 carcinogen was not processed in Toxtree – Pb2+ 12
IN SILICO PERFORMANCE - DEREK NEXUS
Knowledge-base expert system
Process against all genotoxicity endpoints: mutagenicity, chromosome damage, genotoxicity and carcinogenicity
DEREK NEXUS EXPERIMENTAL CARCINOGENICITY
Positive Negative Total
Positive 174 91 265 Sensitivity = 66%
Negative 64 70 134 Specificity = 52%
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IN SILICO PERFORMANCE - OECD (Q)SAR TOOLBOX
Freely available tool developed by the OECD – not predicting the carcinogenicity
DNA binding profiling
OECD TOOLBOX EXPERIMENTAL CARCINOGENICITY
Positive Negative Total
Positive 173 91 264* Sensitivity = 65%
Negative 76 58 134 Specificity = 57%
*1 carcinogen was not processed in OECD Toolbox – Pb2+ 14
CONSENSUS MODELLING - PREDICTIONS
DEREK Nexus, OECD toolbox and TOXTREE
Integration of the predictions from the three models
25 carcinogens are not predicted (2 of these are metals – excluded from TTC approach)
A total of 23 carcinogens would be missed, i.e. 9%
Number of Compounds
Ames in vivo MN Carcinogenicity
12
7
3
1
Positive
Negative
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SUMMARY OF CARCINOGENIC CHEMICALS MISSED BY THE IN SILICO APPROACH
Number of Chemicals
Clastogenicity in vitro and in vivo
in silico predictivity compared with in vitro genotoxicity
2 Yes – clear positive in vitro and in vivo
Would be predicted by in vitro genetic tox tests but not QSAR
1 No, but Ames positive Would be predicted by in vitro genetic tox tests but not QSAR
3 Negative in vitro assays. Weak positive / questionable in vivo MN assays.
Negative in in vitro genetic tox tests and also QSAR.
An evaluation of 2 of the chemicals indicated that these were negative in genotoxicity assays, which suggests they were falsely categorised.
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CONCLUSIONS
If take worst case view 5 genotoxic carcinogens (positive in vivo MN data) were not predicted by in silico approaches Three of these were not detected by in vitro genetic tox methods
Additional 4 genotoxic and carcinogenic materials (positive Ames) with no alert in silico
9 in total
2% probability (based on this dataset) of supporting a genotoxic carcinogen (at exposures of 90 mg/person/day or above), based on Cramer classification
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1.5 mg/kg bw/day
CONCLUSIONS
The TTC approach is a pragmatic exposure-driven risk assessment tool, and is of particular use where compound specific data may be limited
The presence of structural alerts for genotoxicity/carcinogenicity restricts the internal exposure to 0.15mg/person/day
An integrated suite of 3 in silico prediction models (DEREK Nexus, OECD (Q)SAR TOOLBOX and TOXTREE) could be useful as a screen for potential genotoxicity/carcinogenicity, with an absence of alerts used to support chemicals at higher exposure levels using the Cramer decision tree
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0.0025 mg/kg bw/day
ACKNOWLEDGEMENTS
Nora Aptula
Phil Carthew
Catherine Clapp
Claire Davies
Paul Fowler
David Mason
Claire Moore
Diana Suarez Rodriguez
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