Computational Toxicology: Methods and Applications for Risk Assessment

Computational Toxicology: Methods and Applications for Risk Assessment is an essential reference on the translation of computational toxicology data into information that can be used for more informed risk assessment decision-making. This book is authored by leading international investigators who have real-world experience in relating computational toxicology methods to risk assessment. Key topics of interest include QSAR modeling, chemical mixtures, applications to metabolomic and metabonomic data sets, toxicogenomic analyses, applications to REACH informational strategies and much more. The examples provided in this book are based on cutting-edge technologies and set out to stimulate the further development of this promising field to offer rapid, better and more cost-effective answers to major public health concerns.

Authored by leading international researchers engaged in cutting-edge applications of computational methods for translating complex toxicological data sets into useful risk assessment informationIncorporates real-world examples of how computational toxicological methods have been applied to advance the science of risk assessment Provides the framework necessary for new technologies and fosters common vocabularies and principles upon which the effects of new chemical entities should be compared

FOREWORD 
1. INTRODUCTION
2. PBPK, QSAR and TOXICITY PATHWAYS: CHEMICAL SCREENING  AND PRIORITZATION TOOLS
3. COMPUTATIONAL RISK ASSESSMENT OF UNTESTED HAZARDOUS CHEMICAL AGENTS RELEASTED IN THE WATER ENVIRONMENT
4. RISK ASSESSMENT OF CHEMICAL MIXTURES
5. MODELING SENSITIVE SUB-POPULATIONS FOR RISK ASSESSMENT
6. COMPUTATIONAL METHODS FOR TOXICOGENOMIC ANALYSES FOR RISK ASSESSMENT
7. INTEGRATED SYSTEMS BIOLOGY APPROACHES TO PREDICTING DRUG-INDUCED LIVER TOXICITY
8. COMPUTATIONAL TRANSLATION AND INTEGRATION OF TEST DATA TO MEET RISK ASSESSEMENT GOALS
9. COMPUTATIONAL TRANSLATION OF DATA FROM NON-MAMMALIAN SPECIES TO MEET REACH INFORMATIONAL STRATEGIES
10. DEVLOPMENT OF IN SILICO TISSUE MODELS FOR RISK ASSESSMENT
11. EXAMPLES OF SIMULATIONS WITH A NEWLY DEVELOPED GENERIC  PBTK –MODEL FOR INCORPORATING HUMAN BIOMONITORING  DATA TO MEET REACH GUIDELINES
12. USE OF PUBLIC DATA SETS for RISK ASSESSMENT 
13. COMPUTATIONAL TOXICOLOGY AND APPLICATIONS FOR RISK ASSESSMENTS OF PHARMACEUTICALS
14. DECISION FOREST: A NOVEL PATTERN RECOGNITION METHOD FOR IN SILICO RISK ASSESSMENT
15. TRANSLATION OF COMPUTATIONAL MODEL RESULTS
16. FUTURE RESEARCH NEEDS