Computational Toxicology

Foreword

References

List of Contributors

Chapter 1. Introduction

Chapter 2. Quantitative Structure-Activity Relationship (QSAR) Models, Physiologically Based Pharmacokinetic (PBPK) Models, Biologically Based Dose Response (BBDR) and Toxicity Pathways: Computational Tools for Public Health

Introduction

Application of Structure-Activity Relationship (SAR) and Quantitative Structure-Activity Relationship (QSAR)

Physiologically Based Pharmacokinetic (PBPK) Modeling Case Studies

VOC Models

Metals Models

References

Chapter 3. Multiple Chemical Exposures and Risk Assessment

Historical Perspective

Regulatory Perspective

Mixtures versus Components

Additivity Approaches

Future Directions

References

Chapter 4. Modeling of Sensitive Subpopulations and Interindividual Variability in Pharmacokinetics for Health Risk Assessments

Introduction

Physiological Differences and PBPK Modeling of Sensitive Human Subpopulations

Animal PBPK Models for Evaluating Sensitive Subpopulations

Concluding Remarks

Disclaimer

References

Chapter 5. Integrated Systems Biology Approaches to Predicting Drug-Induced Liver Toxicity: A Dynamic Systems Model of Rat Liver Homeostasis Combined with In Vitro Measurements to Predict In Vivo Toxicity

Introduction

General Principles

Model Building

Energy Homeostasis

Glutathione Homeostasis

Fatty Acid Metabolism

Bile Salt Metabolism and Transport

Solving the Equation-Set

Model Validation and Predictions

Conclusions

References

Chapter 6. Computational Translation and Integration of Test Data to Meet Risk Assessment Goals

Introduction

Computational Analysis and Translational Research

Toxicology-Based (Q)SARs

Read-Across

Data Mining for Computational Translation and Integration of Test Data

High-Throughput Screening for Signal Detection in Risk Assessment

Integrating Computational Tools with Test Data for Risk Assessment

Disclaimer

References

Chapter 7. Computational Translation of Nonmammalian Species Data to Mammalian Species to Meet REACH and Next Generation Risk Assessment Needs

A Changing Regulatory Environment

Nonmammalian Species Can Help to Reduce, Refine, and Replace Mammalian Animal Testing

Pathway-Based Hazard and Risk Assessment

Translating Effects on Nonmammalian Species to Mammalian Species

Translating Molecular Initiating Events: Gene/Protein Annotation and Mammalian Ortholog Identification

Annotation of Large Gene Sets

Pathway-Level Comparison/Translation

Pathway-Based Extrapolation to Mammals in Determining Chemical Mode of Action

Pathway-Based Dose-Response Relationships

Network Inference and Mapping

Cross-Species Analysis Using Networks

Translating Effects through Computational Modeling at the Systems Level

Future Efforts in Use of High-Throughput Screening and “Omics” Technology and Computational Tools in Translation of Nonmammalian Species to Mammalian Species to Meet REACH and Next Generation Risk Assessment Needs

References

Chapter 8. Interpretation of Human Biological Monitoring Data Using a Newly Developed Generic Physiological-Based Toxicokinetic Model: Examples of Simulations with Carbofuran and Methyl Ethyl Ketone

Introduction

The Generic PBTK Model IndusChemFate

Examples

Discussion

Supplementary Information

References

Chapter 9. Uses of Publicly Available Data in Risk Assessment

Introduction

Publicly Available Data Sets with Uses in Risk Assessment

Comparison of the NHANES IV and ToxCast™ Data Sets

Methods for Compiling Data from Multiple Sources for Risk Assessment

Designing Publicly Available Toxicological Data Sets

Analogies to the Human Genome Project in Computational Toxicology

Chemical Domain and Limitations to Data Analysis of Traditional and Computational Toxicology Data

Data Semantics and Limitations to Relating HTS Data to In Vivo Effects

Conclusions

References

Chapter 10. Computational Toxicology Experience and Applications for Risk Assessment in the Pharmaceutical Industry

Background

Two Main Considerations

Summary

References

Chapter 11. Omics Biomarkers in Risk Assessment: A Bioinformatics Perspective

Abbreviations and Glossaries

Introduction

Biomarkers

Bioinformatics Approaches: Challenges and Solutions in Omics Biomarker Discovery

Decision Forest for Omics Biomarkers

Conclusion

Disclaimer

References

Chapter 12. Translation of Computational Model Results for Risk Decisions

Origins and Nature of the Computational Toxicology Applications in Risk Assessment

Drivers for the Application of Computational Toxicology to Risk Assessment

Translational Research

Computational Toxicology Applications in Risk- and Hazard-Based Screening

Current Status of Computational Toxicology in Quantitative Risk Assessment

Summary

References

Chapter 13. Future Directions for Computational Toxicology for Risk Assessment

Needed Essential Elements

Specific Elements in Computational Toxicology Needed for the Field to Move Forward

Index