High-Throughput Screening Methods in Toxicity Testing (ePub)

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.