294
R. Huang
data seem to be the best choice for ADE or human in vivo toxicity prediction. The
DTA-based models, however, cannot be applied to predict new compounds without
such annotations available. It is therefore important to generate high-quality assay
data with good coverage of the biological space and validation of these datasets.
14.5 Conclusions and Future Directions
The Tox21 program is a multiagency federal collaboration to advance in vitro toxicological testing in the twenty-first century. During phase II, the production phase, a
battery of in vitro assays with target-specific and mechanism-based readouts has been
developed, validated, and adapted to a quantitative high-throughput screening platform. The Tox21 10K compound collection has been successfully screened against
a panel of over 50 nuclear receptor and stress response pathway assays, generating
over 85 million publicly available data points as a rich resource for toxicology.
These high-quality datasets have proven instrumental in identifying mechanisms
of compound toxicity and developing models for predicting in vivo toxicity response.
While in vitro assay data alone showed limited predictive power of adverse human
effects, complementing the biological space coverage with additional targets, in the
continuation of the Tox21 program, showed promise to significantly improve the
performance of the assay data-based models resulting in robust models for human
toxicity prediction. All results provide rich datasets to researchers for further data
mining, generation of new hypotheses, and developing new methods for activity
modeling. The predictive computational models generated from these high-quality
datasets can help shed light on the potential of using in vitro assays as an alternative
approach for assessing chemical toxicity.
References
1. NTP (2014) Current directions and evolving strategies
2. Collins FS, Gray GM, Bucher JR (2008) Toxicology. Transforming environmental health protection. Science 319(5865):906–907
3. Kavlock RJ, Austin CP, Tice RR (2009) Toxicity testing in the 21st century: implications for
human health risk assessment. Risk Anal 29(4):485–487 (Discussion 492–487)
4. NRC (2007) Toxicity testing in the 21st century: a vision and a strategy. In: Council NR (ed),
The National Academies Press, Washington, DC
5. Tice RR, Austin CP, Kavlock RJ, Bucher JR (2013) Improving the human hazard characterization of chemicals: a Tox21 update. Environ Health Perspect 121(7):756–765
6. PubChem (2013) Tox21 phase II compound collection [updated 2013; cited 4 Dec 2013].
Available from http://www.ncbi.nlm.nih.gov/pcsubstance/?term=tox21
7. NCATS (2016) Tox21 data browser [cited 2016]. Available from https://tripod.nih.gov/tox21/
8. Attene-Ramos MS, Miller N, Huang R, Michael S, Itkin M, Kavlock RJ, Austin CP, Shinn
P, Simeonov A, Tice RR, Xia M (2013) The Tox21 robotic platform for the assessment of
environmental chemicals—from vision to reality. Drug Discov Today 18(15–16):716–723
R. Huang
data seem to be the best choice for ADE or human in vivo toxicity prediction. The
DTA-based models, however, cannot be applied to predict new compounds without
such annotations available. It is therefore important to generate high-quality assay
data with good coverage of the biological space and validation of these datasets.
14.5 Conclusions and Future Directions
The Tox21 program is a multiagency federal collaboration to advance in vitro toxicological testing in the twenty-first century. During phase II, the production phase, a
battery of in vitro assays with target-specific and mechanism-based readouts has been
developed, validated, and adapted to a quantitative high-throughput screening platform. The Tox21 10K compound collection has been successfully screened against
a panel of over 50 nuclear receptor and stress response pathway assays, generating
over 85 million publicly available data points as a rich resource for toxicology.
These high-quality datasets have proven instrumental in identifying mechanisms
of compound toxicity and developing models for predicting in vivo toxicity response.
While in vitro assay data alone showed limited predictive power of adverse human
effects, complementing the biological space coverage with additional targets, in the
continuation of the Tox21 program, showed promise to significantly improve the
performance of the assay data-based models resulting in robust models for human
toxicity prediction. All results provide rich datasets to researchers for further data
mining, generation of new hypotheses, and developing new methods for activity
modeling. The predictive computational models generated from these high-quality
datasets can help shed light on the potential of using in vitro assays as an alternative
approach for assessing chemical toxicity.
References
1. NTP (2014) Current directions and evolving strategies
2. Collins FS, Gray GM, Bucher JR (2008) Toxicology. Transforming environmental health protection. Science 319(5865):906–907
3. Kavlock RJ, Austin CP, Tice RR (2009) Toxicity testing in the 21st century: implications for
human health risk assessment. Risk Anal 29(4):485–487 (Discussion 492–487)
4. NRC (2007) Toxicity testing in the 21st century: a vision and a strategy. In: Council NR (ed),
The National Academies Press, Washington, DC
5. Tice RR, Austin CP, Kavlock RJ, Bucher JR (2013) Improving the human hazard characterization of chemicals: a Tox21 update. Environ Health Perspect 121(7):756–765
6. PubChem (2013) Tox21 phase II compound collection [updated 2013; cited 4 Dec 2013].
Available from http://www.ncbi.nlm.nih.gov/pcsubstance/?term=tox21
7. NCATS (2016) Tox21 data browser [cited 2016]. Available from https://tripod.nih.gov/tox21/
8. Attene-Ramos MS, Miller N, Huang R, Michael S, Itkin M, Kavlock RJ, Austin CP, Shinn
P, Simeonov A, Tice RR, Xia M (2013) The Tox21 robotic platform for the assessment of
environmental chemicals—from vision to reality. Drug Discov Today 18(15–16):716–723