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Related Experiment Videos

Systems-ADME/Tox: resources and network approaches.

Sean Ekins1

  • 1GeneGo, 500 Renaissance Drive, Suite 106, St. Joseph, MI 49085, USA. sean@genego.com

Journal of Pharmacological and Toxicological Methods
|August 2, 2005
PubMed
Summary
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Drug development costs can be reduced by using toxicogenomics to identify harmful compounds early. This approach integrates complex data for a better understanding of molecular effects on biological systems.

Area of Science:

  • Pharmacology
  • Computational Biology
  • Toxicology

Background:

  • High drug development costs stem from late identification of undesirable compounds.
  • High-throughput screening generates large datasets, necessitating advanced analysis.
  • Systems biology and pathway software enable analysis of high-throughput data in cellular context.

Purpose of the Study:

  • To review current data generation in ADME/Tox.
  • To introduce computational approaches for ADME/Tox.
  • To highlight the potential of systems-ADME/Tox by integrating diverse data and technologies.

Main Methods:

  • Toxicogenomics integrates complex, multidimensional datasets.
  • Network algorithms and curated interaction databases are applied.

Related Experiment Videos

  • Systems biology methods are utilized for data analysis.

    • Main Results:

    • Toxicogenomics offers a more complete understanding of molecular effects on biological systems.
    • Computational approaches, including network algorithms, are crucial for analyzing complex toxicogenomic data.
    • Integration of these tools leads to systems-ADME/Tox.

    Conclusions:

    • Systems-ADME/Tox, integrating toxicogenomics and computational methods, is essential for early identification of undesirable compounds.
    • Understanding available data resources and technologies is key to successful implementation.
    • Network technologies applied to drug transporters and metabolizing enzymes demonstrate the power of this approach.