The difficulties associated with making risk assessments on the basis of experimental results are familiar to practitioners in many fields engineering, epidemiology, chemistry, etc. These difficulties are particularly common in problems that have dynamic and stochastic characteristics driven by multiple purposes and goals, with complex interconnections and inter dependencies. Acquiring an appropriate data base, processing and analyzing model results, and transmitting these results at an appropriate technical, social, political, and institutional level are additional difficulties that must be addressed. This book is grounded on the premise that risks are best assessed on the basis of experimental results and sound mathematical analyses, coupled with the knowledge of experts. The carcinogenicity prediction and battery selection (ePBS) approach described herein provides a systematic mechan ism-a synthesis of systems and statistical and decision analyses-to aid researchers and decision makers in the critical field of carcinogenicity prediction in selecting an appropriate battery of tests to use and in translating experimental results into information that can be used as an aid to decision making.
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I Basics of the CPBS Approach to Risk Assessment and Decision Making.- 1 The Carcinogenicity Prediction and Battery Selection Approach.- 1.1. Introduction.- 1.2. Overview of the CPBS Methodology.- 1.3. The Cancer Hazard Identification Problem.- References.- 2 Fundamental Basics of the CPBS Approach.- 2.1. Bayesian Decision Analysis.- 2.2. Cluster Analysis.- 2.3. Multiple-Objective Decision Making.- 2.4. Dynamic Programming.- References.- II Carcinogenicity Prediction and Battery Selection Methodology.- 3 Preliminary Analysis.- 3.1. Data Base Considerations.- 3.2. Analysis of Test Performance.- 3.3. Exploratory Analysis of the Data.- 3.4. Testing for Dependencies among Tests.- References.- 4 Battery Selection.- 4.1. Computing Measures of Battery Performance.- 4.2. Battery Selection Using Enumeration.- 4.3. A Heuristic Approach for Constructing Batteries with Good Performance.- 4.4. A Strategy for Constructing Batteries Using Dynamic Programming.- 4.5. Dynamic Programming for Construction of Non-dominated Batteries.- References.- 5 Risk Assessment Using Test Results.- 5.1. Making Predictions When Tests Are Conditionally Independent.- 5.2. Making Predictions When Tests Are Conditionally Dependent.- Reference.- 6 Applications of CPBS to Cancer Hazard Identification.- 6.1. Introduction.- 6.2. An Illustration of CPBS Prediction on Acrylamide.- 6.3. Battery Selection Considerations.- 6.4. CPBS and Decision Analysis.- 6.5. Closing Remarks.- References.- Epilogue.- Appendix. List of Abbreviations for Bioassays and Short-Term Tests.
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