barcelona april, 2008 overview of the qsar application toolbox gilman veith international qsar...

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

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nMany Mechanisms Give Similar Trends

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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


Fillingdata gap

ReportEndpoints


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


Fillingdata gap

ReportEndpoints


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


Fillingdata gap

ReportEndpoints


General characterization by the following grouping schemes:• Substance information:

•CAS•Name•Structural formula•OECD Global portal

Chemicalinput


Fillingdata gap

ReportEndpoints


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


Fillingdata gap

ReportEndpoints


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


Fillingdata gap

ReportEndpoints


General characterization by the following grouping schemes:

• Substance information• Predefined• Mechanistic• Empirical:

•Chemical elements•Groups of elements•Natural functional groups•AIM (EPA/SRC)

Chemicalinput


Fillingdata gap

ReportEndpoints


Chemicalinput


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


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


Fillingdata gap

ReportEndpoints


Forming and Pruning Categories:

• Predefined•OECD categorization•US EPA categorization•Inventory affiliation•Database affiliation•Substance type

Chemicalinput


Fillingdata gap

ReportEndpoints


Data gaps filling approaches• Read-across• Trend analysis• QSAR models

Chemicalinput


Fillingdata gap

ReportEndpoints


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


Fillingdata gap

ReportEndpoints


barcelona april, 2008 overview of the qsar application toolbox gilman veith international qsar...

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