280
R. Huang
CEBS
Chemical Effects in Biological Systems
CYP
Cytochrome P450
DMSO
Dimethylsulfoxide
DTA
Drug Target Annotation
EPA
Environmental Protection Agency
FN
False Negative
FP
False Positive
FDA
Food and Drug Administration
GPCR
G-Protein-Coupled Receptor
HTS
High-Throughput Screening
NCATS
National Center for Advancing Translational Sciences
NCCT
National Center for Computational Toxicology
NIEHS
National Institute of Environmental Health Sciences
NTP
National Toxicology Program
NR
Nuclear Receptor
QC
Quality Control
qHTS
Quantitative High-Throughput Screening
QSAR
Quantitative Structure–Activity Relationship
ROC
Receiver operating characteristic
SOM
Self-Organizing Map
SR
Stress Response
Tox21
Toxicology for the twenty-first Century
TN
True Negative
TP
True Positive
WFS
Weighted Feature Significance
14.1 Introduction
Animal-based in vivo models have been traditionally used to assess the toxicological effects of chemicals, with results extrapolated to foreshadow potentially harmful
events in humans. More than 80,000 chemicals are currently registered for use in the
United States, for 95% of which no data on human exposure and/or hazard is available
[1]. In addition, about 2000 new chemicals are being introduced into our environment
every year that may pose hazards for human health [1]. Traditional toxicity testing
methods rely heavily on low throughput, expensive, and time-consuming animal
studies, making it impossible to evaluate the in vivo toxicity of the fast growing
number of chemicals in a cost-efficient and timely manner. The reliability of extrapolating test results derived from animals to health effects in humans poses another
challenge due to species differences. High-throughput screening (HTS) techniques,
now routinely used in conjunction with computational methods and information
technology to probe how chemicals interact with biological systems, offer a new
alternative to traditional toxicity testing. Through HTS assays, patterns of cellular
R. Huang
CEBS
Chemical Effects in Biological Systems
CYP
Cytochrome P450
DMSO
Dimethylsulfoxide
DTA
Drug Target Annotation
EPA
Environmental Protection Agency
FN
False Negative
FP
False Positive
FDA
Food and Drug Administration
GPCR
G-Protein-Coupled Receptor
HTS
High-Throughput Screening
NCATS
National Center for Advancing Translational Sciences
NCCT
National Center for Computational Toxicology
NIEHS
National Institute of Environmental Health Sciences
NTP
National Toxicology Program
NR
Nuclear Receptor
QC
Quality Control
qHTS
Quantitative High-Throughput Screening
QSAR
Quantitative Structure–Activity Relationship
ROC
Receiver operating characteristic
SOM
Self-Organizing Map
SR
Stress Response
Tox21
Toxicology for the twenty-first Century
TN
True Negative
TP
True Positive
WFS
Weighted Feature Significance
14.1 Introduction
Animal-based in vivo models have been traditionally used to assess the toxicological effects of chemicals, with results extrapolated to foreshadow potentially harmful
events in humans. More than 80,000 chemicals are currently registered for use in the
United States, for 95% of which no data on human exposure and/or hazard is available
[1]. In addition, about 2000 new chemicals are being introduced into our environment
every year that may pose hazards for human health [1]. Traditional toxicity testing
methods rely heavily on low throughput, expensive, and time-consuming animal
studies, making it impossible to evaluate the in vivo toxicity of the fast growing
number of chemicals in a cost-efficient and timely manner. The reliability of extrapolating test results derived from animals to health effects in humans poses another
challenge due to species differences. High-throughput screening (HTS) techniques,
now routinely used in conjunction with computational methods and information
technology to probe how chemicals interact with biological systems, offer a new
alternative to traditional toxicity testing. Through HTS assays, patterns of cellular