Chapter title |
(Q)SAR Methods for Predicting Genotoxicity and Carcinogenicity: Scientific Rationale and Regulatory Frameworks
|
---|---|
Chapter number | 20 |
Book title |
Computational Toxicology
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7899-1_20 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7898-4, 978-1-4939-7899-1
|
Authors |
Cecilia Bossa, Romualdo Benigni, Olga Tcheremenskaia, Chiara Laura Battistelli, Bossa, Cecilia, Benigni, Romualdo, Tcheremenskaia, Olga, Battistelli, Chiara Laura |
Abstract |
Knowledge of the genotoxicity and carcinogenicity potential of chemical substances is one of the key scientific elements able to better protect human health. Genotoxicity assessment is also considered as prescreening of carcinogenicity. The assessment of both endpoints is a fundamental component of national and international legislations, for all types of substances, and has stimulated the development of alternative, nontesting methods. Over the recent decades, much attention has been given to the use and further development of structure-activity relationships-based approaches, to be used in isolation or in combination with in vitro assays for predictive purposes. In this chapter, we briefly introduce the rationale for the main (Q)SAR approaches, and detail the most important regulatory initiatives and frameworks. It appears that the existence and needs of regulatory frameworks stimulate the development of better predictive tools; in turn, this allows the regulators to fine-tune their requirements for an improved defense of human health. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 15 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 3 | 20% |
Researcher | 3 | 20% |
Student > Postgraduate | 1 | 7% |
Student > Master | 1 | 7% |
Unknown | 7 | 47% |
Readers by discipline | Count | As % |
---|---|---|
Pharmacology, Toxicology and Pharmaceutical Science | 2 | 13% |
Nursing and Health Professions | 1 | 7% |
Agricultural and Biological Sciences | 1 | 7% |
Chemistry | 1 | 7% |
Materials Science | 1 | 7% |
Other | 0 | 0% |
Unknown | 9 | 60% |