Chapter title |
Adverse Outcome Pathways as Tools to Assess Drug-Induced Toxicity.
|
---|---|
Chapter number | 14 |
Book title |
In Silico Methods for Predicting Drug Toxicity
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3609-0_14 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3607-6, 978-1-4939-3609-0
|
Authors |
Mathieu Vinken |
Editors |
Emilio Benfenati |
Abstract |
Adverse outcome pathways (AOPs) are novel tools in toxicology and human risk assessment with broad potential. AOPs are designed to provide a clear-cut mechanistic representation of toxicological effects that span over different layers of biological organization. AOPs share a common structure consisting of a molecular initiating event, a series of key events connected by key event relationships, and an adverse outcome. Development and evaluation of AOPs ideally complies with guidelines issued by the Organization for Economic Cooperation and Development. AOP frameworks have yet been proposed for major types of drug-induced injury, especially in the liver, including steatosis, fibrosis, and cholestasis. These newly postulated AOPs can serve a number of purposes pertinent to safety assessment of drugs, in particular the establishment of quantitative structure-activity relationships, the development of novel in vitro toxicity screening tests, and the elaboration of prioritization strategies. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 28 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 7 | 25% |
Researcher | 6 | 21% |
Student > Master | 4 | 14% |
Other | 1 | 4% |
Unspecified | 1 | 4% |
Other | 0 | 0% |
Unknown | 9 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Pharmacology, Toxicology and Pharmaceutical Science | 5 | 18% |
Medicine and Dentistry | 2 | 7% |
Biochemistry, Genetics and Molecular Biology | 2 | 7% |
Environmental Science | 1 | 4% |
Nursing and Health Professions | 1 | 4% |
Other | 5 | 18% |
Unknown | 12 | 43% |