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Use of Toxicological Pathways for Hazard Assessment in OECD (Q)SAR Toolbox:

Use of Toxicological Pathways for Hazard Assessment in OECD (Q)SAR Toolbox:. LMC, Bourgas University, Bulgaria Chemical Management Center, NITE, Japan Fraunhofer Institute for Toxicology and Experimental Medicine, Germany OECD, Environment Directorate, Paris

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Use of Toxicological Pathways for Hazard Assessment in OECD (Q)SAR Toolbox:

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  1. Use of Toxicological Pathways for Hazard Assessment in OECD (Q)SAR Toolbox: LMC, Bourgas University, Bulgaria Chemical Management Center, NITE, Japan Fraunhofer Institute for Toxicology and Experimental Medicine, Germany OECD, Environment Directorate, Paris International QSAR Foundation, USA McKim Conference September 2008, Duluth, USA

  2. Outline • Conceptual framework of QSAR • Categorization and QSAR • Predicting human health endpoints in Toolbox • Molecular initiating events and toxicological pathways • Case study with 28d RDT • Mechanism database in Toolbox

  3. Outline • Conceptual framework of QSAR • Categorization and QSAR • Predicting human health endpoints in Toolbox • Molecular initiating events and toxicological pathways • Case study with 28d RDT • Mechanism database in Toolbox

  4. Conceptual Framework of SAR/QSAR Chemical Speciation and Metabolism Molecular Initiating Events Measurable System Effects Adverse Outcomes Parent Chemical Rather than developing statistical models of complex endpoints, key molecular initiating events become the “well-defined” endpoints for QSAR. Gil Veith; International QSAR Foundation

  5. IQF Framework for QSAR Adverse Outcomes Parent Chemical Black Box Models Rapid but not mechanistically transparent

  6. IQF Framework for QSAR Speciation and Metabolism Molecular Initiating Events Measurable System Effects Adverse Outcomes Parent Chemical QSAR QSAR Systems Biology Chemistry/ Biochemistry 1. Identify Plausible Molecular Initiating Events 2. Design Database for Abiotic Binding Affinity/Rates 3. Explore Linkages in Pathways to Downstream Effects 4. Develop QSARs to Predict Initiating Event from Structure

  7. Outline • Conceptual framework of QSAR • Categorization and QSAR • Predicting human health endpoints in Toolbox • Molecular initiating events and toxicological pathways • Case study with 28d RDT • Mechanism database in Toolbox

  8. Categorization and QSAR • The categories concept is part of the historical description of QSARs • QSARs are quantitative models of key mechanistic processes which result in the measured activity

  9. Categorization and QSAR • Each QSAR estimate is a result of two predictions: • Qualitative prediction of predominant interaction mechanisms and hazard identification (defined by category) • Quantitative prediction of the intensity (potency) of the specific mechanisms of interaction (predicted by QSAR) • Wrong definition for the mechanism of underlying reaction could result in using of a wrong QSAR for the potency estimate

  10. Categorization and QSAR • Example • Phenols are polar narcotics, uncouplers or electrophilic chemicals. • QSAR models for predicting acute effects for each mechanism have comparable uncertainty • The potency of the electrophilic mechanism can be orders of magnitude greater than polar narcotics • Wrong categorization of chemicals could cause significant errors in defining the potency

  11. Categorization and QSAR Basic Assumption for Regulatory Acceptance • The logic for selecting a specific model (category) for a specific chemical is the cornerstone of regulatory acceptance OECD QSAR AD-Hoc group meeting, Madrid, April 2007

  12. Outline • Conceptual framework of QSAR • Categorization and QSAR • Predicting human health endpoints in Toolbox • Molecular initiating events and toxicological pathways • Case study with 28d RDT • Mechanism database in Toolbox

  13. Modelled human health endpoints in Toolbox • Sensitization • Lung • Skin • Genotoxicity • AMES bacterial mutagenicity • Chromosomal aberration • Irritation/corrosion • Eye • Skin

  14. Commonality between the modelled endpoints The effects could be characterized by: • Single toxicological pathway • Strong dependency on initiating molecular events (e.g. on molecular structure) • Small impact of subsequent biological processes (“short” toxicological pathways)

  15. QSAR Framework for modeled endpoint Speciation and Metabolism Molecular Initiating Events Measurable System Effects Adverse Outcomes Parent Chemical QSAR QSAR Biological processes Initiating chemical/Biochemical Interactions

  16. QSAR Framework for modeled endpoint Speciation and Metabolism Molecular Initiating Events Adverse Outcomes Parent Chemical QSAR QSAR Initiating chemical/Biochemical Interactions

  17. Mechanism of skin sensitization Penetration Epidermis Protein conjugates Protein conjugates Metabolism Dermis Hypodermis Lymph Vein • Assumptions in the model: • Chemicals always penetrate stratum corneum • Formation of protein conjugates is a premise for ultimate effect • Metabolism may play significant role in skin sensitization Subject of modeling

  18. Model Simulator of skin metabolism ∩ QSAR models S-Pr S sensitization S-Pr W sensitization QSAR S-Pr S-Pr S sensitization W sensitization Phase II Reactive species Metabolism No sensitization Parent Reactive species Phase II Reactive species

  19. Conclusion: The categorization of substances according to chemical mechanisms governing the initiating reaction with protein or DNA is good enough for predicting human health effects resulting from single and “short” toxicological pathways

  20. Outline • Conceptual framework of QSAR • Categorization and QSAR • Predicting human health endpoints in Toolbox • Molecular initiating events and toxicological pathways • Case study with 28d RDT • Mechanism database in Toolbox

  21. Toolbox logical sequence of components usage Chemical input Profiling Endpoints Category Definition Filling data gap Report • General characterization by the following grouping schemes: • Substance information • Predefined • Mechanistic: • Acute Toxicity MOA (OASIS) • Protein binding (OASIS) • DNA binding (OASIS) • Electron reach fragments (Superfragments) BioBite • Cramer Classification Tree (ToxTree) • Veerhar/Hermens reactivity rules (ToxTree) • Lipinski rules (MultiCase)

  22. Molecular Initiating Events and Toxicological Pathways General Consideration

  23. Molecular Level Mechanism of chemical interactions

  24. Molecular Level Mechanism of chemical interactions Mechanism 1 Mechanism 2 Mechanism 3 …

  25. Molecular Level Mechanism of chemical interactions Mechanism 1 Mechanism 2 Mechanism 3 … Distribution in lipid phase Protein binding Arylcarboxylate aminolysis Michael-type addition Schiff base formation … DNA binding Quinones Hydrazines …

  26. Molecular Level Mechanism of chemical interactions Receptor 1 – Receptor 2 – Receptor 3 – … Mechanism 1 Mechanism 2 Mechanism 3 … Distribution in lipid phase Protein binding Arylcarboxylate aminolysis Michael-type addition Schiff base formation … DNA binding Quinones Hydrazines …

  27. Molecular Level Mechanism of chemical interactions Receptor 1 – Receptor 2 – Receptor 3 – … Mechanism 1 Mechanism 2 Mechanism 3 … • Initiating event/Receptor • Activation of AP-1、NF-kB、EpRE in hepatocyte →Activation of JNK/AP-1 pathway • Activation of estrogen Signals → Proliferation of bile duct cell and hepatocyte injury • Activation of MAPK Signals - Apoptosis • …

  28. Chemistry/Biochemistry Molecular Level Mechanism of chemical interactions Receptor 1 – Receptor 2 – Receptor 3 – … Mechanism 1 Mechanism 2 Mechanism 3 … • Initiating event/Receptor • Activation of AP-1、NF-kB、EpRE in hepatocyte →Activation of JNK/AP-1 pathway • Activation of estrogen Signals → Proliferation of bile duct cell and hepatocyte injury • Activation of MAPK Signals - Apoptosis • …

  29. Chemistry/Biochemistry Molecular Level Cell Level Mechanism of chemical interactions System biology/Effect Receptor 1 – Receptor 2 – Receptor 3 – … Mechanism 1 Mechanism 2 Mechanism 3 …

  30. Chemistry/Biochemistry Molecular Level Cell Level Mechanism of chemical interactions System biology/Effect Receptor 1 – Receptor 2 – Receptor 3 – … System 1 – System 2 – System 3 – ... Mechanism 1 Mechanism 2 Mechanism 3 …

  31. Chemistry/Biochemistry Molecular Level Cell Level Mechanism of chemical interactions System biology/Effect Receptor 1 – Receptor 2 – Receptor 3 – … System 1 – System 2 – System 3 – ... Mechanism 1 Mechanism 2 Mechanism 3 … • System biology • Hepatotoxicity mechanism: • Oxidant stress • Mitochondrial damage • Apoptosis • Degradation of membrane phospholipid • Aberration of ion channel • Increase of enzyme activition of drug metabolism • Inflammatory responses • …

  32. Chemistry/Biochemistry Molecular Level Cell Level Mechanism of chemical interactions System biology/Effect Receptor 1 – Receptor 2 – Receptor 3 – … System 1 – System 2 – System 3 – ... Effect 1 Effect 2 Effect 3 ... Mechanism 1 Mechanism 2 Mechanism 3 … • Cell Effects • Hepatocyte • Changes in the tubular epithelium • …

  33. Chemistry/Biochemistry System biology Molecular Level Cell Level Mechanism of chemical interactions System biology/Effect Receptor 1 – Receptor 2 – Receptor 3 – … System 1 – System 2 – System 3 – ... Effect 1 Effect 2 Effect 3 ... Mechanism 1 Mechanism 2 Mechanism 3 …

  34. Chemistry/Biochemistry System biology Symptomology Tissue, Organ and Body Observed Effects Molecular Level Cell Level Mechanism of chemical interactions System biology/Effect Receptor 1 – Receptor 2 – Receptor 3 – … System 1 – System 2 – System 3 – ... Effect 1 Effect 2 Effect 3 ... Mechanism 1 Mechanism 2 Mechanism 3 …

  35. Chemistry/Biochemistry System biology Symptomology Tissue, Organ and Body Observed Effects Molecular Level Cell Level Mechanism of chemical interactions System biology/Effect Tissue Effect 1 Effect 2 Effect 3 ... Organ Effect 1 Effect 2 Effect 3 ... Body Effect 1 Effect 2 Effect 3 ... Receptor 1 – Receptor 2 – Receptor 3 – … System 1 – System 2 – System 3 – ... Effect 1 Effect 2 Effect 3 ... Mechanism 1 Mechanism 2 Mechanism 3 …

  36. Chemistry/Biochemistry System biology Symptomology Tissue, Organ and Body Observed Effects Molecular Level Cell Level Mechanism of chemical interactions System biology/Effect Tissue Effect 1 Effect 2 Effect 3 ... Organ Effect 1 Effect 2 Effect 3 ... Body Effect 1 Effect 2 Effect 3 ... Receptor 1 – Receptor 2 – Receptor 3 – … System 1 – System 2 – System 3 – ... Effect 1 Effect 2 Effect 3 ... Mechanism 1 Mechanism 2 Mechanism 3 … Molecular initiating event(s) and subsequent downstream effects

  37. Chemistry/Biochemistry System biology Symptomology Tissue, Organ and Body Observed Effects Molecular Level Cell Level Mechanism of chemical interactions System biology/Effect Tissue Effect 1 Effect 2 Effect 3 ... Organ Effect 1 Effect 2 Effect 3 ... Body Effect 1 Effect 2 Effect 3 ... Receptor 1 – Receptor 2 – Receptor 3 – … System 1 – System 2– System 3 – ... Effect 1 Effect 2 Effect 3 ... Mechanism 1 Mechanism 2 Mechanism 3 … Molecular initiating event(s) and subsequent downstream effects

  38. Chemistry/Biochemistry System biology Symptomology Tissue, Organ and Body Observed Effects Molecular Level Cell Level Mechanism of chemical interactions System biology/Effect Tissue Effect 1 Effect 2 Effect 3 ... Organ Effect 1 Effect 2 Effect 3 ... Body Effect 1 Effect 2 Effect 3 ... Receptor 1 – Receptor 2 – Receptor 3 – … System 1 – System 2– System 3 – ... Effect 1 Effect 2 Effect 3 ... Mechanism 1 Mechanism 2 Mechanism 3 … Molecular initiating event(s) and subsequent downstream effects

  39. Conclusion: • One complex endpoint (e.g., 28days RDT) could be conditioned by more than one toxicological pathway (blood toxicity, liver damage, kidney damage) • (Q)SAR models should be associated with a single toxicological pathway • Chemicals which interact by different toxicological pathways should be out of the model mechanistic domain

  40. Conclusion: The categorization of substances according to chemical mechanisms governing the initiating reactions with protein or DNA is not enough for predicting human health effects resulting from multiple and complex toxicological pathways • The link between chemical and toxicological mechanisms and respective categorization schemes needs to be identified

  41. Outline • Conceptual framework of QSAR • Categorization and QSAR • Predicting human health endpoints in Toolbox • Molecular initiating events and toxicological pathways • Case study with 28d RDT • Mechanism database in Toolbox

  42. Case study: Twenty-eight day repeat dose oral toxicity test of chemicals (28d RDT) • Data produced by: • Safety examination of existing chemicals in NITE- Japan; under Japanese Chemical Substances Control Law; • Fraunhofer Institute for Toxicology and Experimental Medicine, Hanover, Germany 2. Categorization of chemicals for predicting 28d RDT is based on analysis of data by NITE and LMC

  43. 28-day RDT tests conducted on male rats that tested 14 aromatic amines

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