Ambit2 training Workshop Brussels, Sept 29, 2017
Meeting the Global Challenge of Applying New Scientific Methods to Improve Environmental and Human Health Risk Assessments
REACH-loaded LRI Cheminformatic system AMBIT2 supporting read-across
Dr. Bruno Hubesch Cefic LRI, Programme Consultant
1 LRI Mission
• Advance approaches for assessing the safety of chemicals • Improve our understanding of the potential health and environmental risks • Work with partners in governmental agencies, academia, and industry • Build effective scientific networks linking research to practice and policy • Tailor its research to adapt to changing issues in chemical risk • Address public concerns to improve their confidence in our products • Leader in chemical safety assessment research • Support high-quality science to inform effective decision making by industry, regulators, and society. Three Regional Programs: - Europe (CEFIC) - United States (ACC) -Japan (JCIA)
Annual ICCA LRI Workshop 3 http://lri.americanchemistry.com/LRI-Research-Program/Research- Strategies/ICCA-LRI-Global-Research-Strategy.pdf
4 2015-2016
Innovating Chemical Testing Understanding Everyday Exposures Translating Research Outcomes for Product Safety CEFIC Innovate methods to link Develop predictive models to Support model development and information at the molecular estimate exposures from integration to facilitate ecological level, such as epigenetics, to biomonitoring data risk assessment health and environmental Evaluate effects of cumulative Review and promote methods to impacts and aggregate exposures use epidemiologic data to Support the 3Rs – replace, involving dermal exposure and understand complex health reduce, and refine – for animal consumer products effects testing
ACC Advance application and Develop predictive models for Translate high-throughput data extrapolation of cell-based estimating consumer exposures to real-world contexts and testing methods for human and screening and prioritizing applications, to facilitate risk- health risk assessments new chemicals based decision making Incorporate exposure and dose Improve interpretation of Advance approaches to better information to advance biomonitoring data for understand the scientific basis of interpretation and modeling of application to estimating epidemiological studies linking data from high-throughput cumulative exposures health effects to chemical assays exposures JCIA Develop and evaluate new Develop predictive and practical Assess the effects of chemicals testing methods, such as those models for estimating on ecosystems and the that use biomarkers, to improve occupational exposures environment assessment of chemicals and Monitor and predict potential Evaluate the safety of new products exposures from environmental chemical substances, such as Innovate high-throughput and in pathways nanomaterials, to promote vitro methods to facilitate responsible industrial chemical evaluation of genotoxicity of management large numbers of chemicals 5 Priorities: 7 key questions for the next 5-10 years Executing the long-term refocus of the LRI Key questions (< 10y)
1. Omics / 21st Century Toxicology: How to link information at molecular level to health impacts and interpreting results for meaningful decision making?
2. Predictive tools for health impact: What are pragmatic approaches for reducing complexity, whilst maintaining robust predictions of health effects?
3. Combination effects: How to identify combination effects scenarios of concern?
4. Eco-systems approach: Which new concepts enhance ecological relevance of risk assessment?
5. Real life Exposure: Which predictive, validated exposure scenarios apply to assessing environmental stressors?
6. Comparative assessment: How to interpret impact of health and environmental stressors?
7. Benefit to risks approaches: Can we understand societal drivers for public acceptance of innovation? 7 8
Read-across and Category formation
Non-testing methods which are regularly applied to assess the safety of Chemicals . Used on average in 20% of the Endpoint Study Records, while QSAR is used in < 1% Accepted by most Regulatory Bodies if the approach taken is sufficiently justified and documented Supported by in-silico tools (see ECETOC, 2012, TR 116) . Using various methodologies like QSARs, rule-based predictions , similarity tools, etc. Why LRI AMBIT https://ambitlri.ideaconsult.net/ . An in-silico tool developed continuously since 2005 (http://ambit.sourceforge.net) . Goal of the LRI EEM9.3-IC project was enhancing the predictive power of AMBIT . Using large datasets of quality Substance data: ECHA & company DB & other sources . Implementing workflows for Assessments supporting the assessor in setting up a read across/category approach and in establishing a valid justification for the approach . Minimizing overall animal testing and resource costs by using available studies for other substances as well if appropriate 8 CEFIC LRI AMBIT Chemoinformatics System
Transfer via Other Web service or *.i5z files Databases Data transfer
Company IUCLID DB Data & ECHA IUCLID DB transfer as Major Data Sources LRI AMBIT Supporting Read across & Category formation Data transfer Transfer Other of 14570 Tools Dossiers
9 AMBIT2 ?
OpenFoodTox database from EFSA VEGA (courtesy E.Benfenati, Mario Negri Institute, Milano Open source, Application Programming Interface available Stand alone and web versions IUCLID6 compatible New and better functionalities And more…
10 Acknowledgements CEFIC LRI EEM9.3-IC Project idea for LRI EEM9.3-IC o Volker Koch, Clariant (retired) o Joanna Jaworska, P&G (AMBIT 2005) Project input : Clariant CompTox Team o Udo Jensch (Toxicologist) o Volker Koch (Ecotoxicologist) o Qiang Li (Toxicologist) o Joachim Schneider-Reigl (Ecotoxicologist) Project implementation o Ideaconsult Ltd. www.ideaconsult.net
Nina Jeliazkova, Nikolay Kochev
11 1 2
Acknowledgement
CEFIC LRI would like to thank ECHA for providing the non- confidential IUCLID data which are accessible on the ECHA Website
Datasets on 14570 Substances have been provided on January 12, 2016 by ECHA in Computer readable format
allowing the import into AMBIT 12 Global marketing campaign /AMBIT2
1. EU/Brussels, April 20, 2017 (Article) Chemical Watch, “|Cefic’s AMBIT software tool reaching users around the globe” 2. EU/Helsinki, June 15-16, 2017: (Talk) ECOPA-SSCT Workshop 2017/CAAT-EU Academy, “Tools for Read-Across” 3. US/ Seattle, August 20-24, 2017: (Poster) WC10 / 10th World Congress on Alternatives & Animal Use
4. Launch campaign, Week Sept 4, 2017: LRI mailing list, website, Cefic Newsroom, Twitter, etc..
5. EU/Bratislava, September 11-14, 2017:(Poster) EUROTOX 2017
6. EU/Brussels, Sept 29, 2017: Hands-on Training Workshop at Cefic
7. EU/Brussels, Oct 5-6, 2017: (Talk) CAAT-EU Academy, “Use of in silico tools in chemical’s hazard assessment”
8. EU/Milano, October 19, 2017 : (Talk) LIFE COMBASE Workshop on in silico methods and biocides, Milan, PROSIL/LIFE project workshop (Mario Negri)
13 Global marketing campaign /AMBIT
1. EU/Brussels/Jan: training WS at Cefic 2. EU/Brussels/Feb: (Talk) CAAT-EU / Cefic LRI WS 3. US/Washington/March: (Talk) CAAT-US /Cefic LRI WS 4. EU/ Finland, Helsinki, 19-20 April 2016: (Poster) Topical Scientific Workshop - New Approach Methodologies in Regulatory Science
5. US/ Florida, Miami, 13-17 June 2016: (Poster) 17th International Conference on QSAR in Environmental and Health Sciences
6. JP/Awaji Island, Japan, 15-16 June 2016: (Talk) Meeting the Global Challenge of Applying New Scientific Methods to Improve Environmental and Human Health Risk Assessments
7. KO/Seoul, South Korea, 13-15 July 2016: (Talk at) 14th International Nanotech Symposium & Nano-Convergence Expo, NANO KOREA 2016
8. EU/Helsinki, Finland, 1-2 September 2016: (Training/isntallation) ECHA
9. EU/Sevilla, Spain, 5-8 September 2016: (Poster at) EUROTOX 2016
10. EU/Milano, Italy, 21 September 2016: (Talk at) PROSIL/LIFE project workshop (Mario Negri)14 1 Dr. Qiang Li, Clariant, 29.09.2017
Workshop on CEFIC LRI Project EEM9.4 LRI AMBIT with IUCLID6 support and extended search capabilities
Why AMBIT2 is good 2 Dr. Qiang Li, Clariant, 29.09.2017
General aspects on non-testing approaches
Options that registrants use to cover REACH information requirements for different data endpoints
Extract from “The use of alternatives to testing on animals for the REACH Regulation” Third Report under Article 117(3) of the REACH Regulation 3 Dr. Qiang Li, Clariant, 29.09.2017
Computational Toxicology
Non-testing approaches are used to fill gaps in Human and Environmental Safety Assessment (ECETOC, 2012 TR116) :
To avoid animal testing Reduce resource costs Bridge the gap of laboratory capacity availability
Read-across and Category formation • Are Non-testing methods which are regularly applied to assess the safety of Chemicals and are accepted by most Regulatory Bodies if the approach taken is sufficiently justified and documented • Is supported by in-silico tools (see ECETOC, 2012, TR 116) using various methodologies like • QSARs, Expert systems allowing rule-based predictions , databases, etc. 4 Dr. Qiang Li, Clariant, 29.09.2017
What is AMBIT2? – Cheminformatics Data Management System
– Developed within the CEFIC LRI EEM9 Project and is part of the LRI Toolbox (http://www.cefic-lri.org/lri-toolbox).
– Free software
– AMBIT2 consists of a database including more than 450.000 chemical structures and REACH dataset of 14.570 substances 5 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT2 main functions – Search structures & Data exact, similar, substructure combined with data search New – Retrieval and management of IUCLID6 substance data substance identification and composition Assigning structures to constituents, impurities … 43 data endpoints of 14.570 substances New – Read across/category formation Workflows facilitates search for target and source structures, generating data matrices, gap filling and generating assessment reports with predefined formats automatically
– Prediction tools / databases New New VEGA models, Toxtree, Cramer rules, Protein binding / OpenFoodToxData – Data management & exchange flexible import/export of dataset manual upload of i6z files exported from IUCLID or semi-automatic import via IUCLID Web services. New 6 Dr. Qiang Li, Clariant, 29.09.2017
IUCLID and Ambit2
Data transfer
Company IUCLID DB CEFIC LRI AMBIT ECHA IUCLID DB Chemoinformatics As System Major Data Source
Search for data Supporting possible but Read across not for structures & Category formation 7 Dr. Qiang Li, Clariant, 29.09.2017 8 Dr. Qiang Li, Clariant, 29.09.2017
Clariant CompTox Architecture
Experts
Other Databases & Tools 9 Dr. QiangConcept Li, Clariant, 29.09.2017 for a AMBIT2 supported substance screening during the R&D process Research candidates for a designated application:
Substance 1 Substance 2 Substance 3 Substance 4 Substance 5
Rest 1 Rest 2 Rest 3 Rest 4 Rest 5 AMBIT2 looks for existing substances with similar structures and with known toxic properties. Experts assess plausibility and refine selection.
Rest 1a Rest 2a Rest 3a Rest 4a Rest 5a
Rest 1b Rest 2b Rest 3b Rest 4b
Rest 1c Rest 2c Rest 4c
Rest 1d Rest 4d
QSAR-Predictions. Causes skin burns, May cause cancer Causes skin irritation Impairs fertility Toxic if swallowed Toxic to aquatic life Experts assess plausibility and make refinements. Experts consider the need of animal testing. Experts make ranking and provide advice. First rank: Most promi- Second rank: accepta- Not recommended for Not recommended for Not recommended for sing candidate for the ble candidate for the further development further development further development intended application intended application 10 Dr. Qiang Li, Clariant, 29.09.2017
Benefits by AMBIT2
– Supporting effective product development - Linking all relevant databases for assessment of chemicals enables initial toxicological assessments before actual product development. – Prevention of the development of substances that serve the purpose but can not be used due to hazardous properties - Improved product safety and cost saving by avoidance of unsuccessful development work. – Improved animal welfare by reduced animal testing - Cost saving by reduced (omitted) animal testing 11 Dr. Qiang Li, Clariant, 29.09.2017 12 Dr. Qiang Li, Clariant, 29.09.2017
Backup 13 Dr. Qiang Li, Clariant, 29.09.2017
Development of new ingredient for a detergent
– The following chemical molecules are considered as candidates
O O O R1 R2 R3 * n O * n O * n O
O O R4 R5 * n O * n O 14 Dr. Qiang Li, Clariant, 29.09.2017
Traditional substance screening during the R&D process
Toxicity test Toxicity test Toxicity test Toxicity test Skin irritation / Skin Reproduction Acute toxicity corrosion sensitization toxicity and …
O go Skin corrosion Development terminated $ R1 * n O $
O go go Skin sensitizing Development terminated $ R2 * n O
O Further development Target R3 go go go go for the intended n O * application
O Development
go go go Teratogenic $
R4 terminated
* n O consuming Money & Time $ Harmful if $ O Development suspended (as Plan B) R5 swallowed * n O 15 CompToxDr. Qiang Li, Clariant, 29.09.2017supported substance screening during the R&D process
CompTox CompTox CompTox Recommend Data Search Read-across Prediction ation
O O
R1a Causes skin burns, Not recommended for R1 * n O * n O Toxic to aquatic life further development O
R1b * n O O
R1c * n O O
R1d * n O O O R2 R a n 2 May cause cancer; * O * n O Not recommended for O Skin sensitising further development
R2b * n O O O First rank: Most R3 No concern n O * R3a * n O promising candidate for Target the intended application O
O R4a Impairs fertility Not recommended for * n O R4 further development * n O O
R4b * n O O
R4c * n O O
R4d * n O
O O Harmful if swallowed Second rank: acceptable R5 R5a candidate for the * n O n O * intended application 1 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Workshop on CEFIC LRI Project EEM9.4 LRI AMBIT with IUCLID6 support and extended search capabilities
AMBIT2 Project Overview
Nina Jeliazkova Ideaconsult Ltd. Sofia,Bulgaria Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
AMBIT2 project Overview Goal of the LRI Project EEM9.3/9.4 was enhancing the predictive power of AMBIT
. Using large datasets of high quality Substance data . Implementing workflows for Assessments supporting the assessor in setting up a read across/category approach and in establishing a valid justification for the approach taken as requested by authorities . Minimizing overall animal testing and resource costs means using available studies for other substances as well if appropriate
2 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
AMBIT2 project Overview Integration of large datasets of high quality Substance data . From a IUCLID Database owned by a company itself . From ECHA IUCLID Database (non-CBI Disseminated data) . From other reliable and quality checked data sources Integration of external prediction tools . From a IUCLID Database owned by a company itself . From ECHA IUCLID Database (non-CBI Disseminated data) . From other reliable and quality checked data sources . Integration of external tools and datasets
3 4 Public, LRI PROJECT EEM9.3LINKING AMBIT WITH IUCLID Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Data transfer AMBIT FUNCTIONS Assigning structures -to constituents, impurities … Search structures & Data - exact, similar, substructure - combined with data search Read across and CEFIC LRI AMBIT category formation Chemoinformatics -Workflows supporting the user Company IUCLID DB System Prediction tools ECHA IUCLID DB -Cramer rules, Protein binding etc As Data analysis tools Major Data Source Supporting -Regressions, clustering etc. Read across Data management Search for data & Category formation -flexible import/export of data possible but Data exchange not for structures - manual or automated Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
REACH: “Chemical substance, a material with a definite chemical composition” http://echa.europa.eu/documents/10162/13643/nutshell_guidance_substance_en.pdf The REACH definition of a substance encompasses all forms of substances and materials on the market, including nanomaterials; and may have complex composition. – Mono-constituent: A substance with one main constituent. – Multi-constituent: A substance with two or more main constituents. - Main constituent: A constituent, not being an additive or impurity, in a substance that makes up a significant part of that substance. Contributes to the naming of the substance. Concentration ofMost the main in constituent(s)-silico tools = purity and of chemical the substance. structure databases do not support – Additive: A substance that has been intentionally added to stabilise the substance.substance Contributes compositions to the substance composition. and relate – Impurity: An unintendedone structure constituent to present a substance in a substance, ! as produced. Does not contribute to the naming of the substance non-confidential REACH data supplied by ECHA
http://ambitlri.ideaconsult.net5 6
Substance and Composition
http://iuclid.eu http://ambit.sf.net
Every Substance in IUCLID is Chemical structures and properties characterized by at least one composition. only (till 2013) A Composition consists of Updated AMBIT data model CONSTITUENTS n>= 1 Substance composition IMPURITIES n>=0 Measured properties assigned to ADDITIVES n>=0 substances A IUCLID substance itself has no chemical Calculated properties assigned to structure. Only constituents, impurities and additives have a structure. structures As a IUCLID composition has at least of 1 When the IUCLID composition is constituent, at least one structure is transferred, AMBIT assigns assigned. Most IUCLID substances are automatically searchable related to more than 1 structure. structures to constituents, impurities and additives
6 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
IUCLID Substance Data in AMBIT Composition Data in AMBIT allow a straightforward overview on constituents, impurities & additives as well as the concentrations associated
Constituent
Impurity
Additive
7 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
IUCLID Substance Data in AMBIT . organized in tab sections allowing easy access by clicking on the tab of interest
The set of templates and fields imported are based on recommendations IUCLID 5.5 XML schema by the Clariant Endpoint study records : 126 OECD Harmonized CompTox team templates (OHT) Endpoint summaries (79 OHT) Large and complex data model IUCLID 6 XML schema New schema. Supported in AMBIT2 8 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Data Import filter for AMBIT
The filter allow to select which data of an IUCLID substance should be imported into AMBIT Applicable for manual data import from IUCLID5 and IUCLID6 files Support for both IUCLID5 and IUCLID6 web services
9 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
IUCLID Substance Data in AMBIT
Phys-chem section
10 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
IUCLID Substance Data in AMBIT ECOTOX section
11 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
IUCLID Substance Data in AMBIT Environmental fate section
12 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
IUCLID Substance Data in AMBIT TOX section
13 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
The LRI AMBIT tool is loaded with non-confidential REACH data supplied by ECHA to CEFIC-LRI under a specific agreement
– CEFIC LRI would like to thank ECHA for providing the non-confidential IUCLID data which are accessible on the ECHA Website – Datasets on 14570 Substances have been provided on January 12, 2016 by ECHA in Computer readable format allowing the import into AMBIT
14 15 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Overview of the data provided by ECHA and OpenFoodTox (EFSA) 16 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Overview of OpenFoodToxData (EFSA)
Several Excel files • Single chemicals • Mixtures, formulations, polymers • Open/closed assessment groups Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Communications with other systems
Transfer via Other Web service or *.i6z files Databases Data transfer
Company IUCLID DB Data & ECHA IUCLID DB transfer as Major Data Sources LRI AMBIT Supporting Read across & Category formation Data transfer Transfer Other of 14570 Tools Dossiers
17 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Toxtree predictions integrated in AMBIT
Standalone Toxtree at http://toxtree.sf.net
18 19 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
VEGA models integrated in AMBIT Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Assessment Workflow in AMBIT Using a Tab Structure
20 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
New Assessment & Identifier (Tab 1)
21 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Collect structures for Assessment (Tab2)
T = Target, S = Source, CM = Category member
Based on the SMILES code of the Target Diglyme a substructure search was carried out limited to those having substance data 22 Clicking T, S or CM allows to assign the structure for intended purpose Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Working matrix (Tab 4)
Composition section
23 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Model predictions in the working matrix (Tab 4)
Automatic merge with predicted values
(e.g. Toxtree, logP) 24 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Assessment report (Tab 5)
AMBIT has several reporting functions, one is creating an assessment report in Word
25 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities 1 CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
Workshop on CEFIC LRI Project EEM9.4 LRI AMBIT with IUCLID6 support and extended search capabilities
IUCLID Substance Data
Nikolay Kochev Ideaconsult Ltd. Sofia,Bulgaria 2 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
Chemical structure vs. Substance
A chemical structure describes a well-defined molecule.
1,2-dimethoxyethane
Chemicals synthesized in reality are not pure substances. In fact such substances represent mixtures of several components. Therefore real substances can not be associated with an unique structure. In contrast, components (i.e.: constituents, impurities and/or additives) can clearly be characterized by a defined structure in each case. Under REACH, the concept of substance is clearly described. This definition is implemented in the IUCLID data base. 3 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
Substances under REACH
under REACH, a chemical substance is composed of: Constituents (n>=1) Impurities (n>=0) Additives (n>=0) under REACH, a chemical substance can have several compositions, e.g. crude, distilled, etc. under REACH, the type of a chemical substance can be: Either mono-constituent (a substance, defined by its composition, in which one main constituent is present to at least 80% (w/w)). Or multi-constituent (a substance, defined by its composition, in which more than one main constituent is present in a concentration 10% (w/w) and < 80% (w/w))
Or UVCB (Substance of Unknown or Variable composition, Complex reaction products or Biological materials) 4 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
REACH substance definition implemented in IUCLID Example: mono-constituent substance
Three different compositions 5 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
REACH substance definition implemented in IUCLID Example: mono-constituent substance
Three different compositions 6 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
REACH substance definition implemented in IUCLID Example: mono-constituent substance
Three different compositions 7 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
REACH substance definition implemented in IUCLID Example: UVCB N,N-dimethyl-C12-14-(even numbered)-alkyl-1-amines 8 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
REACH substance definition implemented in IUCLID Example: multi-constituent substance The substance has 3 constituents and 3 impurities characterized by different structures 9 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
IUCLID6 support in AMBIT
• Given : Completely new XML schema of all objects • 372 schema files, 111 endpoint study record files • Different approach of linking between objects (compared to IUCLID5) • Implementation • Java classes generated from the XML schema (via JAXB) • AMBIT code to convert the generated classes to the internal data model and be able to store into the database • Use existing code for writing into the database • And existing UI to show the data • Transparent from user point of view: select .i6z or .i5z 10 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
IUCLID6 support in AMBIT
• Files (both IUCLID5 and IUCLID6) • Transparent from user point of view: select .i6z or .i5z • Web services • IUCLID5 (SOAP) and IUCLID6 (REST) • All endpoint study records supported previously (and more) • Potential to support all endpoint study records • The “Test material” is no more a checkbox • Each study record links to a test material (a substance, identified by UUID) • Substance and compositions • Reference substances 11 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
IUCLID6 new composition types
• legal entity composition of the substance (default) • boundary composition of the substance • composition of the substance generated upon use • other: • IUCLID5 composition is migrated to “Legal entity composition” • The composition record includes study information • Introduced mostly because of nanomaterials, as REACH substance is defined by the main constituent • (e.g. all TiO2 materials, regardless of the coatings=one substance) • All different nanoforms are described as different compositions of the same substance • And they have different shape, size, etc (i.e. characterisation) 12 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
Detailed information Composition (1) Every constituent, impurity and additive is described in detail with a “Reference substance” with several identifiers 13 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
Detailed information Composition (2)
The structure associated to the reference substance is stored in the IUICLID as a picture format only which is normally not searchable.
InChI notation could be used for structure identification.
SMILES notation could be used for structure identification only if unique SMILES strings are used both on data import and query definition. 14 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
Full structure support in AMBIT for all substance components
Various chemoinformatics approaches for handling chemical structures 15 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
Motivation to transfer IUCLID data to Ambit chemoinformatic system
IUCLID Limitation: IUCLID allows queries in the substance data but has no functionality to search chemical structures (exact, similar, or substructures). Queries using the SMILES and InChI notation are possible. In addition, IUCLID describes endpoints in very detailed complexity. Extraction of key information relevant for substance evaluation is not convenient.
The IUCLID substance composition and IUCLID endpoint data can be transferred and updated into the Ambit system. During this process structures are assigned automatically to the constituents/impurities/additives of the substance. In contrast to IUCLID, Ambit allows structure and data search. 16 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
Motivation to transfer IUCLID data to Ambit chemoinformatic system
Ambit advantages:
Chemical structure searching: exact, similarity and substructure search; Read-across workflow; Flexible faceted and free text searching for structure and data; Export to various data formats preferred by industry and scientific community; Modelling, data analysing and visualization utilities; Support for chemical substances including nanomaterials; Programmatic access via REST API; User friendly web interface. 17 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
Extracting data from IUCLID Substances which should be transferred to AMBIT have to be flagged in IUCLID In the IUCLID chapter “1.3 Identifiers” company specific flags can be added
Company specific flags examples:
TRA number to identify trade products in the SAP System
Substances will be transferred to Ambit (CompTox – Ambit Transfer)
All Flags will be transferred to Ambit and are searchable in Ambit 18 Public, LRI Project EEM9.3, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
Import criteria to specify which studies will be imported into AMBIT
Where can I find these fields in IUCLID? In each Endpoint study record the relevant fields are located in Administrative Data Data source 19 Public, LRI Project EEM9.3, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC
Why a selection is reasonable?
Only high quality study records of the IUCLID substance itself should be imported into AMBIT, therefore we recommend to select only: Key studies and Supporting studies (Adequacy of Study/Purpose flag/); the flags weight of evidence and disregarded study are not high quality information. Reliability 1 and 2 (Reliability); 3 (not reliable) and 4 (not assignable) are not helpful to characterize the relevant endpoint information. Experimental result (Study result type); Read across information should not be selected, because these information will be transferred with the original IUCLID substance to AMBIT. Study reports, Publications and Review article (Reference type); secondary source and grey literature should not be imported 20 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC Import IUCLID files in AMBIT In Ambit some import filters can be selected 21 Public, IUCLID Substance Data CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC Retrieve substances in AMBIT from IUCLID server In Ambit some import filters can be selected CEFIC Long-range Research Initiative, CEFIC LRI Project EEM9.4-IC 1 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Workshop on CEFIC LRI Project EEM9.4 LRI AMBIT with IUCLID6 support and extended search capabilities
AMBIT Cheminformatics system
Nina Jeliazkova, Nikolay Kochev Ideaconsult Ltd. Sofia,Bulgaria 2 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Content
– Introduction – Substance data integration in AMBIT ( different input formats) – Search functionalities - Structures, substances and endpoint data - Structure standardization , transformation, tautomers – Tools integration – via common API - Toxtree, VEGA, other models, descriptors – User management system to grant access rights via roles – The read across workflow - An use case integrating the above functionalities – IT requirements Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
AMBIT Chemoinformatics System Developed within a CEFIC Long-Range Initiative (LRI) . EEM9.3 (2005,2008), EEM9.3-IC (2013-2015), EEM9.4 (2016-ongoing) . Continuously developed and extended through various projects An Open Source Application with the following functions . Search for structure(s) [exact, similar, substructure] and meta data . Assigning structures to constituents, impurities … . Assessment tools (read across/category formation) . Prediction tools e.g. Toxtree (including Cramer rules , Protein binding, etc.), descriptor calculation, pKa etc; . Data analysis tools e.g. regression, classification, clustering etc; . Data management : flexible import/export of data . Data exchange tools: manual or automated via REST Web services API; . Read across workflow
3 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
AMBIT: Chemical structures database & machine learning with web services API http://ambit.sourceforge.net
4 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
AMBIT : Data integration via common data model
Excel Reports (Excel, spreadsheets Word)
IUCLID5 Other formats (RDF, ISA-TAB, etc.) IUCLID6 JSON Other formats REST API
Free text search ambitlri.ideaconsult.net 6 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
IUCLID6 support in AMBIT2
– IUCLID6: Completely new XML schema of all objects - 372 schema files, 111 endpoint study record files - Different approach of linking between objects (compared to IUCLID5) – Implementation - Java classes generated from the XML schema (via JAXB) - AMBIT code to convert the generated classes to the internal data model and be able to store into the database - Use existing code for writing into the database - And existing UI to show the data – Transparent from user point of view: select .i6z or .i5z 7 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Spreadsheets for substance data import
configurable parser for spreadsheet data templates 8 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
EFSA OpenFoodTox data https://www.zenodo.org/record/344883 • Excel files • Not only chemical structures and data • Relationships between structures • Imported into AMBIT database with the help of a JSON configuration 9 Ideaconsult Ltd. Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Search substances by endpoint data
• Check one or more checkboxes and click the Update results The endpoints are combined by AND.
The results above show there are only two substances having data for the three Endpoints are grouped selected endpoints (Appearance, Melting in four categories point and Dissociation constant), P-Chem, Env Fate although there are Eco Tox, Tox 16 substances with data for appearance, 36 substances with melting point values and 15 substances with dissociation constant 10 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Free text search (experimental) Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
AMBIT Search for Structures & Endpoint data
1) Find Structure(s)
2) Find Substance(s)
3) Display data
11 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Combining information from other data sources and prediction results
The vertical sidebar allows collating data and model information with the search results. 13 Ideaconsult Ltd. Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Structure Diagram Editor
Click to show/hide the editor
The structure editor is JavaScript based. • To use the drawn structure for search, click the Use button. • To show the structure, specified as SMILES in the search bar, click the Draw button. 14 Ideaconsult Ltd. Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Substructure search
The substructure search query can be defined by drawing the structure, selecting a SMARTS from the predefined list of SMARTS, or entering a SMARTS, SMILES or chemical name in the text box 15 Ideaconsult Ltd. Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Substance tab
Use the folder icon to open the details.
The Substanc es tab shows the substances related to the chemical structure, and the role of the chemical structure (last column , e.g. Constituent, Impurity, Additive). 16 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Enabling Structure Search : Structure Standardization
conversion keep the to implicit largest kekulisation hydrogens fragment
+ - - Na O O
H2N O H2N O
(i) molecule neutralization (ii) Custom reaction transformations structure conversion to a canonic Isotopes tautomer cleanup OH OH
HN O H2N O
Output: smiles, InChI N=CCCCC(=O)O
InChI=1/C5H9NO2/c6-4-2-1-3- 5(7)8/h4,6H,1-3H2,(H,7,8) 17 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Canonic tautomer generation (a component of the standardisation procedure)
Input structure Rule instance search Generation of all OH tautomers:
OH H2N O OH
H2N OH
OH HN OH
Canonical Ranking O OH H N 0.0 C(C=CN)C=C(O)O 2 OH HN O -0.1 C(C=CN)CC(=O)O O -0.05 C(CC=N)C=C(O)O HN -0.15 C(CC=N)CC(=O)O 18 Ideaconsult Ltd. Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
• Automatic generation of all tautomeric forms of a given organic compound. • Customizable rules for tautomeric transformations. • The predefined knowledge base covers 1–3, 1–5 and 1–7 proton tautomeric shifts. Typical supported tautomerism rules are keto-enol, imin-amin, nitroso- oxime, azo-hydrazone, thioketo-thioenol, thionitroso-thiooxime, amidine-imidine, diazoamino-diazoamino, thioamide-iminothiol and nitrosamine-diazohydroxide • Simple energy based system for tautomer ranking implemented by a set of empirically derived rules. 19 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Input structure AMBIT TAUTOMER Rule selection and flag settings
OC(O)=C(N)C
Post-generation Generating of tautomeric forms: filtering - Combinatorial method - Combinatorial method improved - Incremental method (IA-DFS) Structure is removed Result
Recursion Ranking
Canonical IDEACONSULT LTD. 19 20 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Structures transformation : AMBIT SMARTS/ SMIRKS
(1) Efficient representation of SMARTS Transformations modes: Queries (full Daylight syntax) (1) single (2) Fast structure isomorphism /mapping/ (2) non-overlapping, (3) Support of recursive SMARTS and (3) non-identical, stereo (4) non-homomorphic or (4) Syntax extensions (5) externally specified list of sites. (5) Parsing of SMIRKS (6) Transformation of the target chemical Recursive expressions explicitly define objects the environment around S atom. 21 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Structure standardization in large datasets
– Flexible standardisation workflow - The rules synchronised with pharma companies – Datasets standardised with AMBIT ( H2020 FET ExCAPE project) - PubChem,ChEMBL,eMolecules,SureChem,ZINC,tox datasets ( > 80 mln compounds) - http://ambit.sf.net/ambitcli_standardisation.html - ExCAPE DB (1 mln compounds, 70 mln SAR data points) , AMBIT- hosted , open access - Possible future integration with LRI AMBIT Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Communications with other systems
Transfer via Other Web service or *.i6z files Databases Data transfer
Company IUCLID DB Data & ECHA IUCLID DB transfer as Major Data Sources LRI AMBIT Supporting Read across & Category formation Data transfer Transfer Other of 14570 Tools Dossiers
22 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
AMBIT Web API /UI for data analysis
Dataset
Models
Visualisation Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
AMBIT Web API / UI for data analysis
Descriptor calculation, feature selection; Classification and regression algorithms; Rule based algorithms; Applicability domain algorithms; Visualization, similarity and substructure queries ; Composite algorithms (workflows); Structure optimization (MOPAC), metabolite generation, tautomer generation, etc.
24 25 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Integration with external tools https://www.vegahub.eu
Command line java application provided by IRFMN 26 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Integration with external tools : VEGA https://ambitlri.ideaconsult.net/tool2/ui/vega
– REST model wrapper – Same API as other models (e.g. Toxtree) – Same user interface – Predictions automatically stored – Straightforward integration with read across matrix 27 Ideaconsult Ltd. Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
AMBIT users management
The authorization is role based. • Default roles: user, data manager, admin, read-across • Roles can be assigned at the users page by admin user 28 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Restricted access to assessments 29 AMBIT2 Hands-on Training Workshop 29.09.2017, Brussels, Belgium Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
The read across workflow: integrated view of data and predictions Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
AMBIT publications and contributing projects
Peer reviewed publications (excerpt) 1. J. Sun, N. Jeliazkova, et al, ExCAPE-DB: an CEFIC LRI EEM9.3 integrated large scale dataset facilitating Big Data . P&G (J.Jaworska), Nina Jeliazkova analysis in chemogenomics, J. Cheminform., vol. 9, n. 1, p. 17, Mar. 2017. CEFIC LRI EEM9.3-IC , EEM9.4 (ongoing) : 2. N. Jeliazkova, et al, The eNanoMapper database for IdeaConsult Ltd., UM, Clariant nanomaterial safety information, Beilstein J. Projects contributed to the Nanotechnol., vol. 6, pp. 1609–1634, Jul. 2015. development 3. N. Kochev, V. Paskaleva, and N. Jeliazkova, AMBIT- . EC FP7 OpenTox (2008-2011) Tautomer: An open source tool for tautomer generation, Mol. Inform., vol. 32, pp. 1–24, 2013. . EC FP7 ToxBank (2011-2015) 4. N. Jeliazkova and V. Jeliazkov, AMBIT RESTful web . EC FP7 eNanoMapper (2014-2017) services: an implementation of the OpenTox application programming interface, J. Cheminform., . EC H2020 ExCAPE (2015-2018) vol. 3, no. 1, p. 18, Jan. 2011. . (and more) 5. N. Jeliazkova, J. Jaworska, and A. Worth, Open Open source libraries Source Tools for Read-Across and Category Formation, in In Silico Toxicology, M. Cronin and J. . The Chemistry Development Kit Madden, Eds. Cambridge: Royal Society of . (and many more) Chemistry, 2010, pp. 408–445.
30 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
can be downloaded or consulted online:
Publicly available https://ambitlrli.ideaconsult.net - Clients only need a web browser More information and download links - http://cefic-lri.org/news/cefic-launches-ambit-chemical-safety-prediction-software/ Installation options LOCAL on a LAPTOP/DESKTOP - Local database, local webserver SERVER (on company INTRANET) - Shared database and web server. Clients only need a web browser. Requirements - Java 7, MySQL 5.7, Web server (servlet container, e.g. Apache Tomcat 7.x) TECHNICAL SUPPORT contact Ideaconsult Ltd, Sofia www.ideaconsult.net , email: [email protected] 31 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities
Acknowledgements
CEFIC LRI EEM9.3-IC/EEM9.4 o Bruno Hubesch Project idea for LRI EEM9.3-IC o Volker Koch, Clariant Project input : Clariant CompTox Team o Udo Jensch (Toxicologist) o Volker Koch (Ecotoxicologist) o Qiang Li (Toxicologist) o Joachim Schneider-Reigl (Ecotoxicologist) Project implementation Ideaconsult Ltd. www.ideaconsult.net
32 Cefic LRI AMBIT2 with IUCLID6 support and extended search capabilities 1 Dr. Qiang Li, Clariant, 29.09.2017
Workshop on CEFIC LRI Project EEM9.4 LRI AMBIT with IUCLID6 support and extended search capabilities
Assessment Workflows for Read Across and Substance Category Formation 2 Dr. Qiang Li, Clariant, 29.09.2017
Overview
• General aspects on non-testing approaches
• Guidance elements of the analogue approach / category formation workflow
• Practical example from the past
• AMBIT elements of the analogue approach / category formation workflow 3 Dr. Qiang Li, Clariant, 29.09.2017
General aspects on non-testing approaches
• General aspects on non-testing approaches
• Guidance elements of the analogue approach / category formation workflow
• Practical example from the past
• AMBIT elements of the analogue approach / category formation workflow 4 Dr. Qiang Li, Clariant, 29.09.2017
General aspects on non-testing approaches REACH
Article 13
1. Information on intrinsic properties of substances may be generated by means other than tests, …
… toxicity, information shall be generated whenever possible by means other than vertebrate animal tests …
… alternative methods, for example …
… from information from structurally related substances (grouping or read- across).
Article 25
1. In order to avoid animal testing, testing on vertebrate animals for the purposes of this Regulation shall be undertaken only as a last resort. 5 Dr. Qiang Li, Clariant, 29.09.2017
General aspects on non-testing approaches
Options that registrants use to cover REACH information requirements for different data endpoints
Extract from “The use of alternatives to testing on animals for the REACH Regulation” Third Report under Article 117(3) of the REACH Regulation 6 Dr. Qiang Li, Clariant, 29.09.2017
Guidance elements of the analogue approach / category formation workflow
• General aspects on non-testing approaches
• Guidance elements of the analogue approach / category formation workflow
• Practical example from the past
• AMBIT elements of the analogue approach / category formation workflow 7 Dr. Qiang Li, Clariant, 29.09.2017
Guidance elements of the analogue approach / category formation workflow
analogue approach category development
Extract from Guidance on information requirements and chemical safety assessment, Chapter R.6: QSARs and grouping of chemicals 8 Dr. Qiang Li, Clariant, 29.09.2017
Guidance elements of the analogue approach / category formation workflow
analogue approach
START Task Workload Ambit Support Identify potential Step 1 analogue(s) high high Data gathering for the Step 2 analogues high high Evaluation if available Step 3 data are adequat high low Construct a matrix of Step 4 data availability high high Assess the suitability of Step 5 read-across, and fill data high mid gaps
Document the Step 6 read-across mid mid
STOP
Extract from Guidance on information requirements and chemical safety assessment, Chapter R.6: QSARs and grouping of chemicals 9 Dr. Qiang Li, Clariant, 29.09.2017
Practical example from the past
• General aspects on non-testing approaches
• Guidance elements of the analogue approach / category formation workflow
• Practical example from the past
• AMBIT elements of the analogue approach / category formation workflow 10 Dr. Qiang Li, Clariant, 29.09.2017
Practical example from the past
Data matrix for mammalian toxicity
Naphtol AS Pigment Category
Pigment Red XY
Not skin sensitising
Skin sensitization 11 Dr. Qiang Li, Clariant, 29.09.2017
Practical example from the past
Data matrix for mammalian toxicity
Naphtol AS Pigment Category
Number of fields to be filled for mammalian toxicity (16 category members, 17 endpoints): 272
Additional fields have to be filled for:
• physicochemical properties • environmental fate • environmental toxicity 12 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
• General aspects on non-testing approaches
• Guidance elements of the analogue approach / category formation workflow
• Practical example from the past
• AMBIT elements of the analogue approach / category formation workflow 13 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach /category formation workflow 14 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
• Step 1: Identify potential analogue(s) 15 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
• Step 1: Identify potential analogue(s) 16 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
• Step 1: Identify potential analogue(s) 17 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
• Step 1: Identify potential analogue(s) 18 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
• Step 1: Identify potential analogue(s) 19 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
• Step 1: Identify potential analogue(s) 20 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
• Step 1: Identify potential analogue(s) 21 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
• Step 2: Data gathering for analogues 22 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
• Step 2: Data gathering for analogues 23 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach / workflow
• Step 3: Evaluation of available data for adequacy 24 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
Step 3: Evaluation of available data for adequacy Step 4: Construct a matrix of data availability 25 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
Step 4: Construct a matrix of data availability Step 5: Assess the adequacy of read-across and fill data gap
Θ 26 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
Step 4: Construct a matrix of data availability Step 5: Assess the adequacy of read-across and fill data gap 27 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
Step 6: Document the read-across 28 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
Step 6: Document the read-across 29 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
Step 6: Document the read-across 30 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
Step 6: Document the read-across 31 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
Step 6: Document the read-across 32 Dr. Qiang Li, Clariant, 29.09.2017
CONCLUSION
In contrast to the traditional procedure for analogue approach and category formaion, AMBIT enables the assessor to generate
• more consistent, • high-quality reports,
• involving less efforts and • spending less time. 33 Dr. Qiang Li, Clariant, 29.09.2017 34 Dr. Qiang Li, Clariant, 29.09.2017
Backup 35 Dr. Qiang Li, Clariant, 29.09.2017
Guidance elements of the analogue approach / category formation workflow
analogue approach category development
Extract from Guidance on information requirements and chemical safety assessment, Chapter R.6: QSARs and grouping of chemicals 36 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
– Step 1: Identify potential analogue(s)
Search structures and associated data Search IUCLID substances by identifiers Search IUCLID substances by endpoint data 37 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
– Step 1: Identify potential analogue(s) 38 Dr. Qiang Li, Clariant, 29.09.2017
AMBIT elements of the analogue approach workflow
– Step 1: Identify potential analogue(s) 1 Dr. Qiang Li, Clariant, 29.09.2017
Workshop on CEFIC LRI Project EEM9.4 LRI AMBIT with IUCLID6 support and extended search capabilities
AMBIT Demonstration 2 Dr. Qiang Li, Clariant, 29.09.2017
1. Basic functions of AMBIT
Log in
Search structures and associated data
Search substances by identifiers
Search substances by endpoint data
Import&Export
Toxtree predictions
VEGA predictions 3 Dr. Qiang Li, Clariant, 29.09.2017
2: Assessment Workflow Read Across
Ambit assessment: 1. Category Glymes - Initial target: diglyme - CAS: 111-96-6 - EC: 203-924-4 - SMILES: COCCOCCOC 2. Category Dimethyl Amines - Initial target: N,N-dimethyldodecan-1-amine - CAS: 112-18-5 - EC: 203-943-8 - SMILES: CCCCCCCCCCCCN(C)C 4 Dr. Qiang Li, Clariant, 29.09.2017
Backup 5 Dr. Qiang Li, Clariant, 29.09.2017
Structure examples
CAS Name SMILE Remark
111-96-6 diglyme COCCOCCOC With substance data
127-19-5 dimethylacetamide CC(=O)N(C)C With derek data
103-33-3 Diphenyldiazene C1=CC=CC=C1N=NC=2 Azo compound, for C=CC=CC=2 structure draw, similarity and substructure search
58-08-2 Caffeine CN1C=NC2=C1C(=O)N( EPA FHM, DEREK C)C(=O)N2C
60-11-7 Butter Yellow N(=NC1=CC=C(C= OpenFoodToxData C1)N(C)C)C=2C=C C=CC2 6 Dr. Qiang Li, Clariant, 29.09.2017
Substance examples
Substance Name UUID Public Name Composition
Glymes_Diethylene glycol IUC5-a438545b-3c6c-403f- Diglyme Monoconstituent substance dimethyl ether_(DEGDME, 83e6-5cd2756d77d6 Containing diglyme (CAS 111-96- Diglyme)_ICS_MSe_DE71 6) as constituent Glymes_Ethylene glycol IUC5-eb8957ab-538b-48b6- Monoglyme Monoconstituent substance dimethyl ether_(EGDME, a024-e9875fbd48b1 Containing monoglyme (CAS Monoglyme)_ICS_MSe_DE7 110-71-4) as constituent 1 CLN_N,N-dimethyl-C12-14- IUC5-03298b59-d29b-4670- N,N-dimethyl-C12-14-(even UVCB (even numbered)-alkyl-1- numbered)-alkyl-1-amines a92a-c70f2bceec52 Containing: CAS112-18-5; 112- amines 69-6 etc. as constituent 1 Dr. Qiang Li, Clariant, 29.09.2017
Workshop on CEFIC LRI Project EEM9.4 LRI AMBIT with IUCLID6 support and extended search capabilities
Hands on AMBIT2 functionality 2 Dr. Qiang Li, Clariant, 29.09.2017
Log in Info
– Link: https://ambitlri.ideaconsult.net – Username: workshop – Password: ambit2 – Please use the latest versions of browsers 3 Dr. Qiang Li, Clariant, 29.09.2017
Practical exercises
Exact Search – Search structures using chemical names “Caffeine”, “caffei” (fragment search)
– Search structure using CAS No. 111-96-6 and display substances containing this structure as constituent/impurity
– Search structure in OpenFoodToxData database using SMILES “CCOC(=O)N” 4 Dr. Qiang Li, Clariant, 29.09.2017
Practical exercises
Similarity and substructure search – Draw the following structure using the structure editor and search similar structures 5 Dr. Qiang Li, Clariant, 29.09.2017
Practical exercises
Substance search – Search substance “Triglyme” and check the available composition and endpoint data
– Search substances which have LD50 values > 5000 (oral) and are not mutagenic (in- vitro) 6 Dr. Qiang Li, Clariant, 29.09.2017
Practical exercises
– Run VEGA Models and Toxtree prediction for the following chemical
– Create an assessment for Category amines, C12-18-alkyldimethyl (e.g. “N,N- dimethylhexadecan-1-amine”, CAS 112-69-6) with regard to genetic toxicity in-vivo and short-term toxicity to fish 7 Dr. Qiang Li, Clariant, 29.09.2017
Results 8 Dr. Qiang Li, Clariant, 29.09.2017
Results – Search structures using chemical names “Caffeine”, “caffei” (fragment search) 9 Dr. Qiang Li, Clariant, 29.09.2017
Results
– Search structure using CAS No. 111-96-6 and display substances containing this structure as constituent/impurity 10 Dr. Qiang Li, Clariant, 29.09.2017
Results
– Search structure in OpenFoodToxData database using SMILES “CCOC(=O)N” 11 Dr. Qiang Li, Clariant, 29.09.2017
Results Similarity and substructure search – Draw the following structure using the structure editor and search similar structures
1. 5. 7. 2. & 6. 4.
3. 12 Dr. Qiang Li, Clariant, 29.09.2017
Results
– Search substance “Triglyme” and check the available composition and endpoint data 13 Dr. Qiang Li, Clariant, 29.09.2017
Results
– Search substances which have LD50 values > 5000 (oral) and are not mutagenic 14 Dr. Qiang Li, Clariant, 29.09.2017
Results
– Run VEGA Models and Toxtree prediction for the following chemical 15 Dr. Qiang Li, Clariant, 29.09.2017
VEGA models Prediction 16 Dr. Qiang Li, Clariant, 29.09.2017
Toxtree Prediction 17 Dr. Qiang Li, Clariant, 29.09.2017
Results
– Create an assessment for Category amines, C12-18-alkyldimethyl (e.g. “N,N- dimethylhexadecan-1-amine”, CAS 112-69-6) with regard to genetic toxicity in-vivo and short-term toxicity to fish
– Results: see the following assessment in the public server: