UID:
almahu_9949697927202882
Umfang:
1 online resource (533 p.)
ISBN:
1-281-00384-0
,
9786611003845
,
0-08-047532-9
Inhalt:
Quantitative Structure-Activity Relationship (QSAR) for Pesticide Regulatory Purposes stems from the experience of the EC funded project DEMETRA. This project combined institutes involved in the regulatory process of pesticides, industries of the sector and scientists to develop and offer original software for the prediction of ecotoxicity of pesticides. Then to be used within the dossier preparation for pesticide registration. The basis of this book is more than three-years of research activities, discussions, studies and successful models. This experience represents a useful example n
Anmerkung:
Description based upon print version of record.
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Front Cover; Quantitative Structure-Activity Relationships (QSAR) for Pesticide Regulatory Purposes; Copyright Page; Table of Contents; Forewords; The DEMETRA Project: An Innovative Contribution to Regulatory QSAR; Reference; Preface; The Pesticides and their Ecotoxicological Properties; Moving Forwards the use of QSAR to Predict Toxicological Properties; The DEMETRA Project; The Book Chapters; Acknowledgement; Disclaimer; References; CHAPTER 1 QSARs for regulatory purposes: the case for pesticide authorization; 1. Overview of the Current Pesticide Authorization Procedure
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1.1. Description of the current pesticide legislation (EU Directive 91/414/EEC)1.2. Outline of the ecotoxicology tests required for pesticide authorization under 91/414/EEC; 1.3. How frequently are certain studies submitted and how many studies are submitted to address an Annex point?; 1.4. What changes are likely to occur that could alter the frequency and number of toxicity studies submitted?; 2. Introduction on QSARS for Pesticides; 3. Regulatory Perspectives in the use of QSARs; 3.1. Current use of QSARs in regulation
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3.2. Potential barriers for using QSARs in the pesticide authorization procedure3.3. End-user criteria for the use of QSARs in regulatory assessment; 4. Quality Criteria for Modelling Ecotoxicity Data; 4.1. Data quality and precision required; 4.2. Quality criteria to be applied to ecotoxicity data used in a QSAR; 4.3. Degree of precision required of QSARs for pesticide assessments; 5. Toxicity End-Points with a High Potential to be Replaced with a QSAR Approach; 5.1. Data availability; 5.2. Number of animals tested; 5.3. Study costs
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5.4. End-points with high potential for replacement with a QSAR5.5. Priority end-points; References; CHAPTER 2 Databases for pesticide ecotoxicity; 1. Introduction; 2. Data Availability; 2.1. The EPA-OPP database; 2.2. The SEEM database; 2.3. The BBA database; 2.4. Other databases; 3. Selection of the Data; 3.1. Key features in the choice of the database; 3.2. Comparison of the data internally to the database; 4. Data Representation for Predictive Toxicology; 4.1. A public database example: DSSTox; 4.2. Current toxicity database limitations
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4.3. XML-based standards in chemistry and toxicology4.4. PToxML - a simple XML-based description in predictive toxicology; 5. The Characteristics of the Final Data Sets; 6. Conclusions; Acknowledgments; References; CHAPTER 3 Characterization of chemical structures; 1. Introduction; 2. Characterization of Bi-dimensional Structures; 2.1. Preprocessing of compounds in the data set; 2.2. Geometrical isomers; 2.3. Tautomers; 3. Characterization of Tri-dimensional Structures; 3.1. Crystallographic data; 3.2. Conformational searching and energy minimization; 3.3. Stereoisomers
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3.4. Procedure for the quality control of the chemicals and chemical structures
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English
Weitere Ausg.:
ISBN 0-444-52710-9
Sprache:
Englisch
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