Barcelona April, 2008 Overview of the QSAR Application Toolbox Gilman Veith International QSAR Foundation Duluth, Minnesota
Jan 08, 2018
BarcelonaApril, 2008
Overview of the QSAR Application Toolbox
Gilman VeithInternational QSAR Foundation
Duluth, Minnesota
QSAR Foundation GoalsQSAR Foundation Goals
Identify major scientific gaps in QSAR Identify major scientific gaps in QSAR capabilities for modeling regulatory capabilities for modeling regulatory endpoints and develop an agenda to bridge endpoints and develop an agenda to bridge them them
Develop high quality databases for QSAR Develop high quality databases for QSAR modeling (repeated dose, metabolism, modeling (repeated dose, metabolism, nucleophile reactivity profiles)nucleophile reactivity profiles)
Provide QSAR training for regulators, Provide QSAR training for regulators, industrial users and studentsindustrial users and students
QSAR at a GlanceQSAR at a Glance
Chemistry is based on the premise that Chemistry is based on the premise that similar chemicals will have similar chemical similar chemicals will have similar chemical behaviours, including toxic effectsbehaviours, including toxic effects
QSAR is the science of chemical similarity QSAR is the science of chemical similarity and grouping chemicals by mechanismsand grouping chemicals by mechanisms
QSAR methods use a few measurements in QSAR methods use a few measurements in each group to estimate untested chemicalseach group to estimate untested chemicals
QSAR PurposeQSAR Purpose
It is not possible to test and assess all It is not possible to test and assess all chemicals for all known hazardschemicals for all known hazards
Only a small fraction of chemicals are likely Only a small fraction of chemicals are likely to be found to pose significant hazards in to be found to pose significant hazards in any given test guidelineany given test guideline
QSAR is needed to identify chemicals with QSAR is needed to identify chemicals with minimal hazards and focus assessments on minimal hazards and focus assessments on the chemicals posing the greatest hazardsthe chemicals posing the greatest hazards
Illustrating the Small Percentage of Chemicals with Relevant ER Relative Binding Affinity (RBA)
Among the 39,436 TSCA Chemicals
96.63%
0.11%
0.36%
0.23%
1.26%
0.35%1.06%
>100% (42 chemicals)10-100% (143 chemicals)1-10% (91 chemicals)0.1-1% (496 chemicals)0.01-0.1% (138 chemicals)0.001-0.01% (418 chemicals)<0.001% (38,108 chemicals)
RBA
QSAR MethodsQSAR Methods
QSAR fills Data Gaps by first grouping QSAR fills Data Gaps by first grouping chemicals and then using Existing Data chemicals and then using Existing Data within a group to estimate Missing Valueswithin a group to estimate Missing Values
When the chemical group is identified by a When the chemical group is identified by a common mechanism, QSAR models common mechanism, QSAR models accurately describe the trendsaccurately describe the trends
Aquatic Toxicity for NonPolar Industrial Chemicalshave Consistent Trends over 4-5 Orders of Magnitude
-7
-6
-5
-4
-3
-2
-1
0
0 1 2 3 4 5 6
Log P
Log
Mol
ar C
once
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tion
LC50-96hr MATC-30 day Water Solubility
-2 0 2 4 6 8Log P
-8
-6
-4
-2
0
2Lo
g M
olar
Con
cent
ratio
nMany Mechanisms Give Similar Trends
LC50-96hr
Water Solubility
Grouping Chemicals is Known as the Category Approach
• The reliability and transparency of QSAR are based on grouping common mechanisms
• Chemical mechanisms are easily encoded into computers for practical use by assessors
• The OECD Toolbox was created to simplify grouping chemicals and filling data gaps
What do we mean by Chemical Categories?
• A group of chemicals that have some features that are common– Structurally similar e.g. common substructure– Property e.g. similar physicochemical,
topological, geometrical, or surface properties– Behaviour e.g. (eco)toxicological response
underpinned by a common Mechanism of Action
– Functionality e.g. preservatives, flavourings, detergents, fragrances
Substances whose physicochemical, toxicological and ecotoxicological properties are likely to be similar or follow a regular pattern as a result of structural similarity may be considered as a group, or “category” of substances.
Application of the group concept requires that physicochemical properties, human health effects and environmental effects or environmental fate may be predicted from data for a reference substance within the group by interpolation to other substances in the group (read-across approach). This avoids the need to test every substance for every endpoint.
Annex IX of REACH
Organization for Economic Co-operation and Development
QSAR Application Toolbox-filling data gaps using available information-
Training WorkshopBarcelona
QSAR Application ToolboxOrganization for Economic Co-operation and Development
• First “organized” discussions – ‘Red Lobsters’, Duluth - 1992
-filling data gaps using available information- Historical Notes
• Organized actions of EU and OECD – coming with REACH
• The role of the “revolutionary” notions – category, analogues
• OECD and EU Guidance documents on ‘Category’, ‘QSAR’
• Need for translation documents into a working machinery
QSAR Application ToolboxOrganization for Economic Co-operation and Development
• Improve accessibility of (Q)SAR methods and databases
• Facilitate selection of chemical analogues and categories
• Integrate metabolism/mechanisms with categories/(Q)SAR
• Assist in the estimation of missing values for chemicals
-ENV/JM(2006)47
-filling data gaps using available information-
General Objectives
Special thanks to: • DG Environment• European Chemicals Bureau • Danish Ministry of the Environment• US EPA• Environment Canada • NITE Japan• CEFIC• MultiCase (USA)• SRC (USA)
A collaborative effort of all member countries and stakeholders
Typical queries included in the (Q)SAR Application Toolbox
• Is the chemical included in regulatory inventories or existing chemical categories?
• Has the chemical already been assessed by other agencies/organisations?
• Would you like to search for available data on assessment endpoints for each chemical?
• Explore a chemical list for possible analogues using predefined, mechanistic, empiric and custom built categorization schemes?
• Group chemicals based on common chemical/toxic mechanism and/or metabolism?
• Design a data matrix of a chemical category?
Typical Queries included in the (Q)SAR Application Toolbox
• Fill data gaps in a chemical category using:– read-across, – trend analysis or – QSAR models
• Report the results:– Work history– Export the data matrix– IUCLID 5 harmonized templates
Typical Queries included in the (Q)SAR Application Toolbox
System Workflow
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage
User Alternatives for Chemical ID:A. Single target chemical• Name• CAS# • SMILES/InChi• Draw Chemical Structure• Select from User List/InventoryB. Group of chemicals• User List• Inventory• Specialized Databases
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage
User Alternatives for Chemical ID:A. Single target chemical• Name• CAS# • SMILES/InChi• Draw Chemical Structure• Select from User List/InventoryB. Group of chemicals• User List/Inventory• Specialized Databases
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage
Toolbox Inventories:US EPA TSCACanadian DSL OECD HPVCs, US EPA HPVCsEU EINECSJapanese MITIDANISH EPA
General characterization by the following grouping schemes:• Substance information• Predefined• Mechanistic• Empirical• Custom• Metabolism
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage
General characterization by the following grouping schemes:• Substance information:
•CAS•Name•Structural formula•OECD Global portal
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage
General characterization by the following grouping schemes:• Substance information• Predefined:
• US EPA categorization• OECD categorization• Database affiliation • Inventory affiliation• Substance type: polymers, mixtures, discrete, hydrolyzing
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage
General characterization by the following grouping schemes:
• Substance information• Predefined• Mechanistic:
•Acute Toxicity MOA•Protein binding (OASIS)•DNA binding (OASIS)•Electron reach fragments (Superfragments) BioBite•Cramer Classification Tree (ToxTree)•Veerhar/Hermens reactivity rules (ToxTree)•Lipinski rules (MultiCase)
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage
General characterization by the following grouping schemes:
• Substance information• Predefined• Mechanistic• Empirical:
•Chemical elements•Groups of elements•Natural functional groups•AIM (EPA/SRC)
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
Report
Finding Data for SIDS and Other Endpoints• Selecting Data Base(s):
Toolbox databases Publicly available Proprietary databases
Toolbox Links to External Databases (DSSTOX)
• Selecting type of extracting data: Measured Data Estimated Data Both
Endpoints
Logical sequence of components usage
Measured data summary of the Current Toolbox
1. Biodegradation DB – 745 chemicals2. Genotox DB - 5584 chemicals3. ISSCAN Genotox – 873 chemicals4. Skin sensitization DB - 738 chemicals5. Estrogen RBA - 1514 chemicals6. Bioaccumulation DB – 700 chemicals7. ECOTOX database – 5071 chemicals8. ECETOC database – 777 chemicals
Estimated Data Summary of the Current Toolbox
1. Danish EPA DB - data for 165438 chemicals
Forming and Pruning Categories:• Predefined• Mechanistic• Empirical• Custom• Metabolism
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage
Forming and Pruning Categories:
• Predefined•OECD categorization•US EPA categorization•Inventory affiliation•Database affiliation•Substance type
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage
Data gaps filling approaches• Read-across• Trend analysis• QSAR models
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage
Report the results:• QMRF/QPRF• IUCLID 5 Harmonized Templates• SIDS Dossiers (Data matrix)• History of the Toolbox Application• User-Defined Reports• Documentation:
• Description of the system• Description of Category Editor
Chemicalinput
Profiling CategoryDefinition
Fillingdata gap
ReportEndpoints
Logical sequence of components usage