Development of a large-scale chemogenomics database to improve drug candidate selection and to understand mechanisms of chemical toxicity and action

J Biotechnol. 2005 Sep 29;119(3):219-44. doi: 10.1016/j.jbiotec.2005.03.022.


Successful drug discovery requires accurate decision making in order to advance the best candidates from initial lead identification to final approval. Chemogenomics, the use of genomic tools in pharmacology and toxicology, offers a promising enhancement to traditional methods of target identification/validation, lead identification, efficacy evaluation, and toxicity assessment. To realize the value of chemogenomics information, a contextual database is needed to relate the physiological outcomes induced by diverse compounds to the gene expression patterns measured in the same animals. Massively parallel gene expression characterization coupled with traditional assessments of drug candidates provides additional, important mechanistic information, and therefore a means to increase the accuracy of critical decisions. A large-scale chemogenomics database developed from in vivo treated rats provides the context and supporting data to enhance and accelerate accurate interpretation of mechanisms of toxicity and pharmacology of chemicals and drugs. To date, approximately 600 different compounds, including more than 400 FDA approved drugs, 60 drugs approved in Europe and Japan, 25 withdrawn drugs, and 100 toxicants, have been profiled in up to 7 different tissues of rats (representing over 3200 different drug-dose-time-tissue combinations). Accomplishing this task required evaluating and improving a number of in vivo and microarray protocols, including over 80 rigorous quality control steps. The utility of pairing clinical pathology assessments with gene expression data is illustrated using three anti-neoplastic drugs: carmustine, methotrexate, and thioguanine, which had similar effects on the blood compartment, but diverse effects on hepatotoxicity. We will demonstrate that gene expression events monitored in the liver can be used to predict pathological events occurring in that tissue as well as in hematopoietic tissues.

MeSH terms

  • 5-Aminolevulinate Synthetase / biosynthesis
  • Animals
  • Antineoplastic Agents / pharmacology
  • Antineoplastic Agents / toxicity
  • Automation
  • Bile Ducts / pathology
  • Biotechnology / methods*
  • Carmustine / toxicity
  • Computational Biology
  • Databases as Topic
  • Dose-Response Relationship, Drug
  • Down-Regulation
  • Drug Design*
  • Drug Industry / methods*
  • Gene Expression
  • Humans
  • Hyperplasia / etiology
  • Liver / drug effects
  • Male
  • Methotrexate / toxicity
  • Nucleic Acid Hybridization
  • Oligonucleotide Array Sequence Analysis
  • Organ Size
  • Pharmacology / methods
  • RNA / chemistry
  • RNA, Complementary / metabolism
  • Rats
  • Rats, Sprague-Dawley
  • Reticulocytes / cytology
  • Reticulocytes / metabolism
  • Thioguanine / toxicity
  • Time Factors
  • Tissue Distribution
  • Toxicology / methods


  • Antineoplastic Agents
  • RNA, Complementary
  • RNA
  • 5-Aminolevulinate Synthetase
  • ALAS2 protein, human
  • Thioguanine
  • Carmustine
  • Methotrexate