QSAR in Safety Evaluation and Risk Assessment

Preface

1. QSAR facilitating safety evaluation and risk assessment

Part I: Methods and Advances of QSAR

2. Development of QSAR models as reliable computational tools for regulatory assessment of chemicals for acute toxicity

3. Deep learning-based descriptors as input for QSAR

4. Decision Forest – A machine learning algorithms for QSAR modeling

5. Integrated modelling for compound efficacy and safety assessment

6. Deep learning QSAR methods for chemical toxicity prediction and risk assessment

7. Predictive modeling approaches for the risk assessment of persistent organic pollutants: Classical to Machine learning based QSAR Models

8. Machine learning based QSAR for safety evaluation

9. Advances in QSAR through Artificial Intelligence and Machine Learning methods

10. Advances of the QSAR approach as an alternative strategy in the Environmental Risk Assessment

11. QSAR modeling based on graph neural networks

Part II: Tools and Data Sources for QSAR

12. Modeling safety and risk assessment with VEGA HUB

13. Recent advancements in QSAR and Machine Learning Approaches for risk assessment of organic chemicals

14. admetSAR - a valuable tool for assisting safety evaluation

15. QSAR tools for toxicity prediction in risk assessment – a comparative analysis

16. Fast and Efficient Implementation of Computational Toxicology Solutions Using the FlexFilters Platform

17. Annotate a standard dataset for drug-induced liver injury to support developing QSAR models

18. Application of QSAR Models Based on Machine Learning Methods in Chemical Risk Assessment and Drug Discovery

19. EADB – The database providing curated data for developing QSAR models to facilitate assessment of endocrine activity

20. Centralized data sources and QSAR methods for the prediction of idiosyncratic adverse drug reaction

Part III: QSAR models for Safety Evaluation of Drugs and Consumer Products

21. QSAR modeling for predicting drug-induced liver injury

22. The need of QSAR methods to assess safety of chemicals in food contact materials

23. QSAR models for predicting in vivo reproductive toxicity

24. Aryl hydrocarbon receptors and their ligands in human health management

25. Use of in silico protocols to evaluate drug safety

26. QSAR models for predicting cardiac toxicity of dugs

Part IV: QSAR models for Risk Assessment of Chemicals

27. Similarity-based analyses for the false-positive and false-negative chemicals on the second Ames/QSAR international challenge project

28. QSAR Model of Photolysis Kinetic Parameters in Aquatic Environment

29. QSAR models on transthyretin disrupting effects of chemicals

30. QSAR models for toxicity assessment of multicomponent systems

31. Deploying QSAR to discriminate excess toxicity and identify the toxic mode of action of organic pollutants to aquatic organisms

32. QSAR models for prediction of carrying capacity of microplastic towards organic pollutants

33. QSAR models on degradation rate constants of atmospheric pollutants

Part V: QSAR models in Material Science and Other Areas

34. Significance of QSAR in cancer risk assessment of polycyclic aromatic compounds (PACs)

35. QSAR in risk assessment of nanomaterials

36. In silico and in vitro ecotoxicity - QSAR based predictions for the aquatic environment

37. In vitro to in vivo Extrapolation Methods in Chemical Hazard Identification and Risk Assessment

38. QSAR models in marine ecotoxicology