High-Throughput Screening Methods in Toxicity TestingEdizione 1

Explores the benefits and limitations of the latest high-throughput screening methods

With its expert coverage of high-throughput in vitro screening methods for toxicity testing, this book makes it possible for researchers to accelerate and streamline the evaluation and risk assessment of chemicals and drugs for toxicity. Moreover, it enables them to comply with the latest standards set forth by the U.S. National Research Council's "Toxicity Testing in the 21st Century: A Vision and Strategy" and the E.U.'s REACH legislation. Readers will discover a variety of state-of-the-science, high-throughput screening methods presented by a group of leading authorities in toxicology and toxicity testing.

High-Throughput Screening Methods in Toxicity Testing is divided into five parts:

• General aspects, including predicting the toxicity potential of chemicals and drugs via high-throughput bioactivity profiling
• Assessing different cytotoxicity endpoints
• Assessing DNA damage and carcinogenesis
• Assessing reproductive toxicity, cardiotoxicity, and haematotoxicity
• Assessing drug metabolism and receptor-related toxicity

Each chapter describes method principles and includes detailed information about data generation, data analysis, and applications in risk assessment. The authors not only enumerate the advantages of each high-throughput method over comparable conventional methods, but also point out the high-throughput method's limitations and potential pitfalls. In addition, the authors describe current research efforts to make high-throughput toxicity screening even more cost effective and streamlined.

Throughout the book, readers will find plenty of figures and illustrations to help them understand and perform the latest high-throughput toxicity screening methods.

This book is ideal for toxicologists and other researchers who need to implement high-throughput screening methods for toxicity testing in their laboratories as well as for researchers who need to evaluate the data generated by these methods.