Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Opinion
  • Published:

Toxicogenomics and drug discovery: will new technologies help us produce better drugs?

Nature Reviews Drug Discovery volume 1, pages 84–88 (2002)Cite this article

Abstract

Acting on reports in the late 1980s that most drug candidates fail in development, pharmaceutical discovery programmes responded by devising ways to increase the number of chemicals in the pipeline. With discovery now driven primarily by chemistry and high-throughput screening, the biological effects and, in particular, the toxicity of new compounds are largely not appreciated until a compound enters development. Arguably, this paradigm has produced more failures rather than delivering more successes — with more chemicals to examine, much less is known about any single agent before costly development studies are initiated. The emerging field of toxicogenomics is enabling us to ask detailed questions about drug effects very early on, thereby fundamentally changing our approach to drug discovery.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Therapeutic index.
Figure 2: DNA arrays for toxicogenomics.
Figure 3: A compendium showing gene-expression changes induced by 48 different hepatotoxic compounds in the rat.

Similar content being viewed by others

References

  1. Prentis, R. A., Lis, Y. & Walker, S. R. Pharmaceutical innovation by the seven UK-owned pharmaceutical companies (1964–1985). Br. J. Clin. Pharmacol. 25, 387–396 (1988)

    Article  CAS  Google Scholar 

  2. Venkatesh, S. & Lipper, R. A. Role of the development scientist in compound lead selection and optimization. J. Pharm. Sci. 89, 145–154 (2000)

    Article  CAS  Google Scholar 

  3. Schena, M., Shalon, D., Davis, R. W. & Brown, P.O. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467–470 (1995)

    Article  CAS  Google Scholar 

  4. Lockhart, D. J. et al. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nature Biotechnol. 14, 1675–1680 (1996)

    Article  CAS  Google Scholar 

  5. Lockhart, D. J. & Winzeler, E.A. Genomics, gene expression and DNA arrays. Nature 405, S827–S836 (2000)

    Article  Google Scholar 

  6. Hughes, T. R. et al. Functional discovery via a compendium of expression profiles. Cell 102, 109–126 (2000)

    Article  CAS  Google Scholar 

  7. Bartosiewicz, M., Penn, S. & Buckpitt, A. Applications of gene arrays in environmental toxicology: fingerprints of gene regulation associated with cadmium chloride, benzo(a)pyrene, and trichloroethylene. Environ. Health Perspect. 109, 71–74 (2001)

    Article  CAS  Google Scholar 

  8. Bartosiewicz, M. J., Jenkins, D., Penn, S., Emery, J. & Buckpitt, A. Unique gene expression patterns in liver and kidney associated with exposure to chemical toxicants. J. Pharmacol. Exp. Ther. 297, 895–905 (2001)

    CAS  PubMed  Google Scholar 

  9. Bulera, S. J. et al. RNA expression in the early characterization of hepatotoxicants in Wistar rats by high-density DNA microarrays. Hepatology 33, 1239–1258 (2001)

    Article  CAS  Google Scholar 

  10. Cunningham, M. J., Liang, S., Fuhrman, S., Seilhamer, J. J. & Somogyi, R. Gene expression microarray data analysis for toxicology profiling. Ann. NY Acad. Sci. 919, 52–67 (2000)

    Article  CAS  Google Scholar 

  11. Pennie, W. D., Woodyatt, N. J., Aldridge, T. C. & Orphanides, G. Application of genomics to the definition of the molecular basis for toxicity. Toxicol Lett. 31, 353–358 (2001)

    Article  Google Scholar 

  12. Reilly, T. P. et al. Expression profiling of acetaminophen liver toxicity in mice using microarray technology. Biochem. Biophys. Res. Commun. 282, 321–328 (2001)

    Article  CAS  Google Scholar 

  13. Rockett, J. C. et al. Development of a 950-gene DNA array for examining gene expression patterns in mouse testis. Genome Biol. (2000). [http://genomebiology.com/2001/2/4/research/0014/]

  14. Waring, J. et al. Clustering of hepatotoxins based on mechanism of toxicity using gene expression profiles. Toxicol. Appl. Pharmacol. 175, 28–42 (2001)

    Article  CAS  Google Scholar 

  15. Burczynski, M. E. et al. Toxicogenomics-based discrimination of toxic mechanism in HepG2 human hepatoma cells. Toxicol. Sci. 58, 399–415 (2000)

    Article  CAS  Google Scholar 

  16. Waring, J. F., Ciurlionis, R., Jolly, R. A., Heindel, M. & Ulrich, R. G. Microarray analysis of hepatotoxins in vitro reveals a correlation between gene expression profiles and mechanisms of toxicity. Toxicol. Lett. 120, 359–368 (2001)

    Article  CAS  Google Scholar 

  17. Quackenbush, J. Computational analysis of microarray data. Nature Rev. Genet. 2, 418–427 (2001)

    Article  CAS  Google Scholar 

  18. Gupta, S., Husser, R. C., Geske, R. S., Welty, S. E. & Smith, C. V. Sex differences in diquat-induced hepatic necrosis and DNA fragmentation in Fischer 344 rats. Toxicol. Sci. 54, 203–211 (2000)

    Article  CAS  Google Scholar 

  19. Benigni, R. et al. Mutational studies with diquat and paraquat in vitro. Mutat. Res. 68, 183–193 (1979)

    Article  CAS  Google Scholar 

  20. Gasch, A. P. et al. Genomic expression responses to DNA-damaging agents and the regulatory role of the yeast ATR homolog Mec1p. Mol. Biol. Cell 12, 2987–3003 (2001)

    Article  CAS  Google Scholar 

  21. Thomas, R. S. et al. Identification of toxicologically predictive gene sets using cDNA microarrays. Mol. Pharmacol. 60, 1189–1194 (2001)

    Article  CAS  Google Scholar 

  22. Waring, J. R. et al. Identifying toxic mechanisms using DNA microarrays: evidence that an experimental inhibitor of cell adhesion molecule expression signals through the aryl hydrocarbon nuclear receptor. Toxicology (in the press)

  23. Zielinski, N. P. et al. Expression profiling using DNA microarrays reveals a functional antagonism of the peroxisome proliferator activated receptor-α by the protease inhibitor, ritonavir. Abstr. 41st Interscience Conference Antimicrob. Agents Chemother. 229, (American Society for Microbiology, Washington, 2001).

  24. Gerhold, D. et al. Monitoring expression of genes involved in drug metabolism and toxicology using DNA microarrays. Physiol. Genomics 5, 161–170 (2001)

    Article  CAS  Google Scholar 

  25. Stratowa, C. et al. cDNA microarray gene expression analysis of B-cell chronic lymphocytic leukemia proposes potential new prognostic markers involved in lymphocyte trafficking. Int. J. Cancer 91, 474–480 (2001)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work could not have been done without the expert help at Rosetta of C. Roberts and the Guided Solutions Team, R. Stoughton and the Informatics team, P. Linsley and the Advanced Solutions team and D. Kessler and the High-Throughput Hybridization Facility, and the team at North Creek, Washington. Rosetta Inpharmatics is a wholly-owned subsidiary of Merck & Co.

Author information

Authors and Affiliations

  1. Rosetta Inpharmatics, 12040 115th Avenue NE, Kirkland, 98034, Washington, USA

    Roger Ulrich

  2. Vice President at Merck Research Laboratories, Sumneytown Pike, West Point, 19486, Pennsylvania, USA

    Stephen H. Friend

Authors
  1. Roger Ulrich
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stephen H. Friend
    View author publications

    You can also search for this author in PubMed Google Scholar

Related links

Related links

DATABASES

LocusLink

NF-κB

PPAR-α

Medscape DrugInfo

cyclophosphamide

etoposide

methotrexate

ritonavir

FURTHER INFORMATION

International Life Sciences Institute

National Center for Toxicogenomics

Object Management Group

Yeast Microarray Global View

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ulrich, R., Friend, S. Toxicogenomics and drug discovery: will new technologies help us produce better drugs?. Nat Rev Drug Discov 1, 84–88 (2002). https://doi.org/10.1038/nrd710

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrd710

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing