title: Expression profiling of drug response--from genes to pathways.
abstract: Understanding individual response to a drug-what determines its efficacy and tolerability-is the major bottleneck in current drug development and clinical trials. Intracellular response and metabolism, for example through cytochrome P-450 enzymes, may either enhance or decrease the effect of different drugs, dependent on the genetic variant. Microarrays offer the potential to screen the genetic composition of the individual patient. However, experiments are "noisy" and must be accompanied by solid and robust data analysis. Furthermore, recent research aims at the combination of high-throughput data with methods of mathematical modeling, enabling problem-oriented assistance in the drug discovery process. This article will discuss state-of-the-art DNA array technology platforms and the basic elements of data analysis and bioinformatics research in drug discovery. Enhancing single-gene analysis, we will present a new method for interpreting gene expression changes in the context of entire pathways. Furthermore, we will introduce the concept of systems biology as a new paradigm for drug development and highlight our recent research-the development of a modeling and simulation platform for biomedical applications. We discuss the potentials of systems biology for modeling the drug response of the individual patient.
authors.affiliation: Max Planck Institute for Molecular Genetics, Department of Vertebrate Genomics, Berlin, Germany. herwig@molgen.mpg.de
authors.forename: Ralf
authors.initials: R
authors.lastname: Herwig
authors.forename: Hans
authors.initials: H
authors.lastname: Lehrach
mesh_terms: D000818:Animals; D003627:Data Interpretation, Statistical; D005796:Genes / Q000502:physiology; D015894:Genome, Human; D023281:Genomics / Q000639:trends*; D006801:Humans; D009488:Neurosciences / Q000639:trends; D020411:Oligonucleotide Array Sequence Analysis; D010600:Pharmacology / Q000639:trends*; D015398:Signal Transduction / Q000187:drug effects / Q000235:genetics* / Q000502:physiology*; D049490:Systems Biology