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* Predictive Safety Testing Consortium, aiming to identify and clinically qualify safety biomarkers for regulatory use as part of the [[U.S. Food and Drug Administration|FDA's]] "Critical Path Initiative"<ref name=Mattes/>
* Predictive Safety Testing Consortium, aiming to identify and clinically qualify safety biomarkers for regulatory use as part of the [[U.S. Food and Drug Administration|FDA's]] "Critical Path Initiative"<ref name=Mattes/>
* ToxCast, program for Predicting Hazard, Characterizing Toxicity Pathways, and Prioritizing the Toxicity Testing of Environmental Chemicals at the [[United States Environmental Protection Agency]]<ref>{{cite journal |author=Dix DJ, Houck KA, Martin MT, Richard AM, Setzer RW, Kavlock RJ |title=The ToxCast program for prioritizing toxicity testing of environmental chemicals |journal=Toxicol. Sci. |volume=95 |issue=1 |pages=5–12 |date=January 2007 |pmid=16963515 |doi=10.1093/toxsci/kfl103 }}</ref>
* ToxCast, program for Predicting Hazard, Characterizing Toxicity Pathways, and Prioritizing the Toxicity Testing of Environmental Chemicals at the [[United States Environmental Protection Agency]]<ref>{{cite journal |author=Dix DJ, Houck KA, Martin MT, Richard AM, Setzer RW, Kavlock RJ |title=The ToxCast program for prioritizing toxicity testing of environmental chemicals |journal=Toxicol. Sci. |volume=95 |issue=1 |pages=5–12 |date=January 2007 |pmid=16963515 |doi=10.1093/toxsci/kfl103 }}</ref>
*Tox21, a federal collaboration involving the NIH, Environmental Protection Agency (EPA), and Food and Drug Administration (FDA), is aimed at developing better toxicity assessment methods.<ref name="TOX21project">"Toxicology in the 21st century project" http://www.ncats.nih.gov/research/reengineering/tox21/tox21.html</ref> Within this project the toxic effects of chemical compounds on cell lines derived from the [[1000 Genomes Project]] individuals was assessed and associations with genetic markers were determined.<ref name="Abdo2015">{{Cite pmid|25622337}}</ref> Parts of this data was used in the NIEHS-NCATS-UNC DREAM Toxicogenetics Challenge in order to determine methods for cytotoxicity predictions for individuals.<ref name="TOXGenChal">NIEHS-NCATS-UNC-DREAM Toxicogenetics Challenge https://www.synapse.org/#!Synapse:syn1761567</ref><ref name="DeepTox">"Kernel-based Structural and Pharmacological Analoging" (KSPA) wins prediction of average cytotoxicity at the NIEHS-NCATS-UNC DREAM Toxicogenetics Challenge http://www.bioinf.jku.at/research/DeepTox/</ref>


==See also==
==See also==

Revision as of 12:14, 27 April 2015

Toxicogenomics is a field of science that deals with the collection, interpretation, and storage of information about gene and protein activity within particular cell or tissue of an organism in response to toxic substances. Toxicogenomics combines toxicology with genomics or other high throughput molecular profiling technologies such as transcriptomics, proteomics and metabolomics.[1][2] Toxicogenomics endeavors to elucidate molecular mechanisms evolved in the expression of toxicity, and to derive molecular expression patterns (i.e., molecular biomarkers) that predict toxicity or the genetic susceptibility to it.

In pharmaceutical research toxicogenomics is defined as the study of the structure and function of the genome as it responds to adverse xenobiotic exposure. It is the toxicological subdiscipline of pharmacogenomics, which is broadly defined as the study of inter-individual variations in whole-genome or candidate gene single-nucleotide polymorphism maps, haplotype markers, and alterations in gene expression that might correlate with drug responses (Lesko and Woodcock 2004, Lesko et al. 2003). Though the term toxicogenomics first appeared in the literature in 1999 (Nuwaysir et al.) it was already in common use within the pharmaceutical industry as its origin was driven by marketing strategies from vendor companies. The term is still not universal accepted, and others have offered alternative terms such as chemogenomics to describe essentially the same area (Fielden et al., 2005).

The nature and complexity of the data (in volume and variability) demands highly developed processes of automated handling and storage. The analysis usually involves a wide array of bioinformatics and statistics,[3] regularly involving classification approaches.[4]

In pharmaceutical drug discovery and development toxicogenomics is used to study adverse, i.e. toxic, effects, of pharmaceutical drugs in defined model systems in order to draw conclusions on the toxic risk to patients or the environment. Both the EPA and the U.S. Food and Drug Administration currently preclude basing regulatory decision making on genomics data alone. However, they do encourage the voluntary submission of well-documented, quality genomics data. Both agencies are considering the use of submitted data on a case-by-case basis for assessment purposes (e.g., to help elucidate mechanism of action or contribute to a weight-of-evidence approach) or for populating relevant comparative databases by encouraging parallel submissions of genomics data and traditional toxicologic test results.[5]

Public toxicogenomics projects

  • Chemical Effects in Biological Systems - Project hosted by the National Institute of Environmental Health Sciences building a knowledgebase of toxicology studies including study design, clinical pathology, and histopathology and toxicogenomics data.[6]
  • InnoMed PredTox assessing the value of combining results from omics technologies together with the results from more conventional toxicology methods in more informed decision making in preclinical safety evaluation.[7]
  • Open TG-GATEs (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System) is a Japanese public-private effort. They published gene expression and pathology information for more than 170 compounds (mostly drugs).[8]
  • Predictive Safety Testing Consortium, aiming to identify and clinically qualify safety biomarkers for regulatory use as part of the FDA's "Critical Path Initiative"[7]
  • ToxCast, program for Predicting Hazard, Characterizing Toxicity Pathways, and Prioritizing the Toxicity Testing of Environmental Chemicals at the United States Environmental Protection Agency[9]
  • Tox21, a federal collaboration involving the NIH, Environmental Protection Agency (EPA), and Food and Drug Administration (FDA), is aimed at developing better toxicity assessment methods.[10] Within this project the toxic effects of chemical compounds on cell lines derived from the 1000 Genomes Project individuals was assessed and associations with genetic markers were determined.[11] Parts of this data was used in the NIEHS-NCATS-UNC DREAM Toxicogenetics Challenge in order to determine methods for cytotoxicity predictions for individuals.[12][13]

See also

References

  1. ^ The National Academies Press: Communicating Toxicogenomics Information to Nonexperts: A Workshop Summary (2005) [1]
  2. ^ ed. by Hisham K. Hamadeh; Cynthia A. Afshari. (2004). Hamadeh HK, Afshari CA (ed.). Toxicogenomics: Principles and Applications. Hoboken, NJ: Wiley-Liss. ISBN 0-471-43417-5. {{cite book}}: |author= has generic name (help)CS1 maint: multiple names: authors list (link)
    Omenn GS (November 2004). "Toxicogenomics: Principles and Applications". Environ Health Perspect. 112 (16): A962. PMC 1247673.
  3. ^ Mattes WB, Pettit SD, Sansone SA, Bushel PR, Waters MD (March 2004). "Database development in toxicogenomics: issues and efforts". Environ. Health Perspect. 112 (4): 495–505. doi:10.1289/ehp.6697. PMC 1241904. PMID 15033600.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  4. ^ Ellinger-Ziegelbauer H, Gmuender H, Bandenburg A, Ahr HJ (January 2008). "Prediction of a carcinogenic potential of rat hepatocarcinogens using toxicogenomics analysis of short-term in vivo studies". Mutat. Res. 637 (1–2): 23–39. doi:10.1016/j.mrfmmm.2007.06.010. PMID 17689568.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  5. ^ Corvi R, Ahr HJ, Albertini S; et al. (March 2006). "Meeting Report: Validation of Toxicogenomics-Based Test Systems: ECVAM–ICCVAM/NICEATM Considerations for Regulatory Use". Environ Health Perspect. 114 (3): 420–9. doi:10.1289/ehp.8247. PMC 1392237. PMID 16507466. {{cite journal}}: Explicit use of et al. in: |author= (help)CS1 maint: multiple names: authors list (link)
  6. ^ Collins BC, Clarke A, Kitteringham NR, Gallagher WM, Pennington SR (October 2007). "Use of proteomics for the discovery of early markers of drug toxicity". Expert Opin Drug Metab Toxicol. 3 (5): 689–704. doi:10.1517/17425225.3.5.689. PMID 17916055.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  7. ^ a b Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1007/978-1-60327-048-9_11, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with |doi=10.1007/978-1-60327-048-9_11 instead.
  8. ^ Attention: This template ({{cite pmid}}) is deprecated. To cite the publication identified by PMID 25313160, please use {{cite journal}} with |pmid=25313160 instead.
  9. ^ Dix DJ, Houck KA, Martin MT, Richard AM, Setzer RW, Kavlock RJ (January 2007). "The ToxCast program for prioritizing toxicity testing of environmental chemicals". Toxicol. Sci. 95 (1): 5–12. doi:10.1093/toxsci/kfl103. PMID 16963515.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  10. ^ "Toxicology in the 21st century project" http://www.ncats.nih.gov/research/reengineering/tox21/tox21.html
  11. ^ Attention: This template ({{cite pmid}}) is deprecated. To cite the publication identified by PMID 25622337, please use {{cite journal}} with |pmid=25622337 instead.
  12. ^ NIEHS-NCATS-UNC-DREAM Toxicogenetics Challenge https://www.synapse.org/#!Synapse:syn1761567
  13. ^ "Kernel-based Structural and Pharmacological Analoging" (KSPA) wins prediction of average cytotoxicity at the NIEHS-NCATS-UNC DREAM Toxicogenetics Challenge http://www.bioinf.jku.at/research/DeepTox/


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