Ecotoxicological QSARs

1. Front Matter

   Pages i-xxi

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2. Introduction

   1. Front Matter

      Pages 1-1

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   2. Ecotoxicological Risk Assessment in the Context of Different EU Regulations

      • Antonio Juan García-Fernández

      Pages 3-25

   3. A Brief Introduction to Quantitative Structure-Activity Relationships as Useful Tools in Predictive Ecotoxicology

      • Rahul Balasaheb Aher, Kabiruddin Khan, Kunal Roy

      Pages 27-53

   4. Best Practices for Constructing Reproducible QSAR Models

      • Chanin Nantasenamat

      Pages 55-75

   5. Wildlife Sentinels for Human and Environmental Health Hazards in Ecotoxicological Risk Assessment

      • Antonio Juan García-Fernández, Silvia Espín, Pilar Gómez-Ramírez, Emma Martínez-López, Isabel Navas

      Pages 77-94

3. Methods and Protocols

   1. Front Matter

      Pages 95-95

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   2. Importance of Data Curation in QSAR Studies Especially While Modeling Large-Size Datasets

      • Pravin Ambure, M. Natália Dias Soeiro Cordeiro

      Pages 97-109

   3. Machine Learning and Deep Learning Methods in Ecotoxicological QSAR Modeling

      • Giuseppina Gini, Francesco Zanoli

      Pages 111-149

   4. Use of Machine Learning and Classical QSAR Methods in Computational Ecotoxicology

      • Renata P. C. Barros, Natália F. Sousa, Luciana Scotti, Marcus T. Scotti

      Pages 151-175

   5. On the Relevance of Feature Selection Algorithms While Developing Non-linear QSARs

      • Riccardo Concu, M. Natália Dias Soeiro Cordeiro

      Pages 177-194

   6. Got to Write a Classic: Classical and Perturbation-Based QSAR Methods, Machine Learning, and the Monitoring of Nanoparticle Ecotoxicity

      • Ana S. Moura, M. Natália D. S. Cordeiro

      Pages 195-213

   7. Ecotoxicological QSAR Modeling of Nanomaterials: Methods in 3D-QSARs and Combined Docking Studies for Carbon Nanostructures

      • Bakhtiyor Rasulev

      Pages 215-233

   8. Early Prediction of Ecotoxicological Side Effects of Pharmaceutical Impurities Based on Open-Source Non-testing Approaches

      • Anna Rita Tondo, Michele Montaruli, Giuseppe Felice Mangiatordi, Orazio Nicolotti

      Pages 235-269

   9. Conformal Prediction for Ecotoxicology and Implications for Regulatory Decision-Making

      • Fredrik Svensson, Ulf Norinder

      Pages 271-287

   10. Read-Across for Regulatory Ecotoxicology

       • Gulcin Tugcu, Serli Önlü, Ahmet Aydin, Melek Türker Saçan

       Pages 289-304

   11. Methodological Protocol for Assessing the Environmental Footprint by Means of Ecotoxicological Tools: Wastewater Treatment Plants as an Example Case

       • Roberta Pedrazzani, Pietro Baroni, Donatella Feretti, Giovanna Mazzoleni, Nathalie Steimberg, Chiara Urani et al.

       Pages 305-327

4. Case Studies and Literature Reports

   1. Front Matter

      Pages 329-329

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   2. Development of Baseline Quantitative Structure-Activity Relationships (QSARs) for the Effects of Active Pharmaceutical Ingredients (APIs) to Aquatic Species

      • David J. Ebbrell, Mark T. D. Cronin, Claire M. Ellison, James W. Firman, Judith C. Madden

      Pages 331-356

   3. Ecotoxicological QSARs of Personal Care Products and Biocides

      • Kabiruddin Khan, Hans Sanderson, Kunal Roy

      Pages 357-386

This volume focuses on computational modeling of the ecotoxicity of chemicals and presents applications of quantitative structure–activity relationship models (QSARs) in the predictive toxicology field in a regulatory context. The extensive book covers a variety of protocols for descriptor computation, data curation, feature selection, learning algorithms, validation of models, applicability domain assessment, confidence estimation for predictions, and much more, as well as case studies and literature reviews on a number of hot topics. Written for the Methods in Pharmacology and Toxicology series, chapters include the kind of practical advice that is essential for researchers everywhere. 

Authoritative and comprehensive, Ecotoxicological QSARs is an ideal source to update readers in the field with current practices and introduce to them new developments and should therefore be very useful for researchers in academia, industries, and regulatory bodies.

• Predictive toxicology
• Ecotoxicological risk assessment
• Pharmaceuticals
• Industrial chemicals
• Data curation
• Statistical modeling
• Quantitative structure-activity relationship
• ecotoxicology

• Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India

  Kunal Roy

Dr. Kunal Roy is a Professor in the Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India. He has been a recipient of Commonwealth Academic Staff Fellowship (University of Manchester, 2007) and Marie Curie International Incoming Fellowship (University of Manchester, 2013). The fields of his research interest are Quantitative Structure-Activity Relationship (QSAR) and Chemometric Modelingwith application in Drug Design and Ecotoxicological Modeling. Dr. Roy has published about 300 research articles in refereed journals (current SCOPUS h index 40; SCOPUS Author ID 56962764800). He has also coauthored two QSAR related books (Academic Press and Springer), edited five QSAR books (Springer, Academic Press and IGI Global) and published twelve book chapters. Dr. Roy is a Co-Editor-in-Chief of Molecular Diversity (Springer Nature) and Editor-in-Chief of International Journal of Quantitative Structure-Property Relationships (IGI Global). He also serves in different capacities in the Editorial Boards of several International Journals.

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