9 A Pair Ranking (PRank) Method for Assessing Assay …
177
Disclaimer This article reflects the views of the authors and should not be construed to represent
FDA’s views or policies.
References
1. Justice MJ, Dhillon P (2016) Using the mouse to model human disease: increasing validity and
reproducibility. Dis Models Mech 9(2):101–103
2. Perrin S (2014) Make mouse studies work. Nature 507(7493):423–425
3. Williams ES et al (2009) The European Union’s REACH regulation: a review of its history and
requirements. Crit Rev Toxicol 39(7):553–575
4. Schumann R (2002) The seventh amendment to the cosmetics directive: what does DG enterprise want from ECVAM? ATLA Altern Lab Anim 30:213–214
5. Collins FS et al (2008) Transforming environmental health protection. Science
319(5865):906–907
6. Kavlock RJ et al (2009) Toxicity testing in the 21st century: implications for human health risk
assessment. Risk Anal 29(4):485–487
7. Tice Raymond R et al (2013) Improving the human hazard characterization of chemicals: a
Tox21 update. Environ Health Perspect 121(7):756–765
8. Dix DJ et al (2007) The ToxCast program for prioritizing toxicity testing of environmental
chemicals. Toxicol Sci 95(1):5–12
9. Hamburg MA (2011) Advancing regulatory science. Science 331(6020):987–987
10. Chen M et al (2012) A decade of toxicogenomic research and its contribution to toxicological
science. Toxicol Sci 130(2):217–228
11. Qin C et al (2016) Toxicogenomics in drug development: a match made in heaven? Expert
Opinion Drug Metab Toxicol 12(8):847–849
12. Fielden MR et al (2007) A gene expression biomarker provides early prediction and mechanistic
assessment of hepatic tumor induction by nongenotoxic chemicals. Toxicol Sci 99(1):90–100
13. Liu Z et al (2011) Comparative analysis of predictive models for nongenotoxic hepatocarcinogenicity using both toxicogenomics and quantitative structure-activity relationships. Chem Res
Toxicol 24(7):1062–1070
14. Ellinger-Ziegelbauer H et al (2008) Prediction of a carcinogenic potential of rat hepatocarcinogens using toxicogenomics analysis of short-term in vivo studies. Mutat Res/Fundam Mol
Mech Mutagen 637(1–2):23–39
15. Uehara T et al (2008) A toxicogenomics approach for early assessment of potential nongenotoxic hepatocarcinogenicity of chemicals in rats. Toxicology 250(1):15–26
16. Gusenleitner D et al (2014) Genomic models of short-term exposure accurately predict
long-term chemical carcinogenicity and identify putative mechanisms of action. PLoS ONE
9(7):e102579
17. Lee WJ et al (2014) Investigating the different mechanisms of genotoxic and non-genotoxic
carcinogens by a gene set analysis. PLoS ONE 9(1):e86700
18. Herwig R et al (2016) Inter-laboratory study of human in vitro toxicogenomics-based tests
as alternative methods for evaluating chemical carcinogenicity: a bioinformatics perspective.
Arch Toxicol 90(9):2215–2229
19. Huang J et al (2010) Genomic indicators in the blood predict drug-induced liver injury. Pharmacogenomics J 10(4):267–277
20. Liu Z et al (2016) Mechanistically linked serum miRNAs distinguish between drug induced
and fatty liver disease of different grades. Sci Rep 6:23709
21. Ruden DM et al (2017) Frontiers in toxicogenomics in the twenty-first century—the grand
challenge: to understand how the genome and epigenome interact with the toxic environment
at the single-cell, whole-organism, and multi-generational level. Front Genet 8:173
177
Disclaimer This article reflects the views of the authors and should not be construed to represent
FDA’s views or policies.
References
1. Justice MJ, Dhillon P (2016) Using the mouse to model human disease: increasing validity and
reproducibility. Dis Models Mech 9(2):101–103
2. Perrin S (2014) Make mouse studies work. Nature 507(7493):423–425
3. Williams ES et al (2009) The European Union’s REACH regulation: a review of its history and
requirements. Crit Rev Toxicol 39(7):553–575
4. Schumann R (2002) The seventh amendment to the cosmetics directive: what does DG enterprise want from ECVAM? ATLA Altern Lab Anim 30:213–214
5. Collins FS et al (2008) Transforming environmental health protection. Science
319(5865):906–907
6. Kavlock RJ et al (2009) Toxicity testing in the 21st century: implications for human health risk
assessment. Risk Anal 29(4):485–487
7. Tice Raymond R et al (2013) Improving the human hazard characterization of chemicals: a
Tox21 update. Environ Health Perspect 121(7):756–765
8. Dix DJ et al (2007) The ToxCast program for prioritizing toxicity testing of environmental
chemicals. Toxicol Sci 95(1):5–12
9. Hamburg MA (2011) Advancing regulatory science. Science 331(6020):987–987
10. Chen M et al (2012) A decade of toxicogenomic research and its contribution to toxicological
science. Toxicol Sci 130(2):217–228
11. Qin C et al (2016) Toxicogenomics in drug development: a match made in heaven? Expert
Opinion Drug Metab Toxicol 12(8):847–849
12. Fielden MR et al (2007) A gene expression biomarker provides early prediction and mechanistic
assessment of hepatic tumor induction by nongenotoxic chemicals. Toxicol Sci 99(1):90–100
13. Liu Z et al (2011) Comparative analysis of predictive models for nongenotoxic hepatocarcinogenicity using both toxicogenomics and quantitative structure-activity relationships. Chem Res
Toxicol 24(7):1062–1070
14. Ellinger-Ziegelbauer H et al (2008) Prediction of a carcinogenic potential of rat hepatocarcinogens using toxicogenomics analysis of short-term in vivo studies. Mutat Res/Fundam Mol
Mech Mutagen 637(1–2):23–39
15. Uehara T et al (2008) A toxicogenomics approach for early assessment of potential nongenotoxic hepatocarcinogenicity of chemicals in rats. Toxicology 250(1):15–26
16. Gusenleitner D et al (2014) Genomic models of short-term exposure accurately predict
long-term chemical carcinogenicity and identify putative mechanisms of action. PLoS ONE
9(7):e102579
17. Lee WJ et al (2014) Investigating the different mechanisms of genotoxic and non-genotoxic
carcinogens by a gene set analysis. PLoS ONE 9(1):e86700
18. Herwig R et al (2016) Inter-laboratory study of human in vitro toxicogenomics-based tests
as alternative methods for evaluating chemical carcinogenicity: a bioinformatics perspective.
Arch Toxicol 90(9):2215–2229
19. Huang J et al (2010) Genomic indicators in the blood predict drug-induced liver injury. Pharmacogenomics J 10(4):267–277
20. Liu Z et al (2016) Mechanistically linked serum miRNAs distinguish between drug induced
and fatty liver disease of different grades. Sci Rep 6:23709
21. Ruden DM et al (2017) Frontiers in toxicogenomics in the twenty-first century—the grand
challenge: to understand how the genome and epigenome interact with the toxic environment
at the single-cell, whole-organism, and multi-generational level. Front Genet 8:173