The promise of a virtual lab in drug discovery.

To date, the life sciences 'omics' revolution has not lived up to the expectation of boosting the drug discovery process. The major obstacle is dealing with the volume and diversity of data generated. An enhanced-science (e-science) approach based on remote collaboration, reuse of data and methods, and supported by a virtual laboratory (VL) environment promises to get the drug discovery process afloat. The creation, use and preservation of information in formalized knowledge spaces is essential to the e-science approach. VLs include Grid computation and data communication as well as generic and domain-specific tools and methods for information management, knowledge extraction and data analysis. Problem-solving environments (PSEs) are the domain-specific experimental environments of VLs. Thus, VL-PSEs can support virtual organizations, based on the changing partnerships characteristic of successful drug discovery enterprises.

[1]  J. Burbaum,et al.  Proteomics in drug discovery. , 2002, Current opinion in chemical biology.

[2]  Ian Foster,et al.  Grid technologies empowering drug discovery. , 2002, Drug discovery today.

[3]  R. Russell,et al.  Illuminating drug discovery with biological pathways , 2005, FEBS letters.

[4]  Christopher G Newton,et al.  Outsourcing lead optimisation--the quiet revolution. , 2004, Drug discovery today.

[5]  Scott Gustafson,et al.  caCORE: A common infrastructure for cancer informatics , 2003, Bioinform..

[6]  Carole A. Goble,et al.  myGrid: personalised bioinformatics on the information grid , 2003, ISMB.

[7]  John D. Potter,et al.  At the interfaces of epidemiology, genetics and genomics , 2001, Nature Reviews Genetics.

[8]  J. Bard,et al.  Ontologies in biology: design, applications and future challenges , 2004, Nature Reviews Genetics.

[9]  Paul D Lyne,et al.  Structure-based virtual screening: an overview. , 2002, Drug discovery today.

[10]  Tommy Nilsson Virtual laboratories in the life sciences , 2003 .

[11]  Anne E. Trefethen,et al.  e-Science and its implications , 2003, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[12]  Adesh. kaul,et al.  The Impact of Sophisticated Data Analysis on the Drug Discovery Process 2 Heading Sub Head , 2004 .

[13]  David B. Searls,et al.  Data integration: challenges for drug discovery , 2005, Nature Reviews Drug Discovery.

[14]  Eric K. Neumann,et al.  A Life Science Semantic Web: Are We There Yet? , 2005, Science's STKE.

[15]  E. Werner In silico multicellular systems biology and minimal genomes. , 2003, Drug discovery today.

[16]  Sean Martin,et al.  Globally distributed object identification for biological knowledgebases , 2004, Briefings Bioinform..

[17]  Cees T. A. M. de Laat,et al.  VLAM-G: a grid-based virtual laboratory , 2002, Future Gener. Comput. Syst..

[18]  Enrique Canessa,et al.  Virtual laboratory strategies for data sharing, communications and development , 2002, Data Sci. J..

[19]  S. Debowski Knowledge Management , 2005 .

[20]  Ian T. Foster,et al.  The Anatomy of the Grid: Enabling Scalable Virtual Organizations , 2001, Int. J. High Perform. Comput. Appl..

[21]  Russ B Altman,et al.  Indexing pharmacogenetic knowledge on the World Wide Web. , 2003, Pharmacogenetics.

[22]  K. Buetow Cyberinfrastructure: Empowering a "Third Way" in Biomedical Research , 2005, Science.

[23]  David W. Walker,et al.  The software architecture of a distributed problem‐solving environment , 2000 .

[24]  H. Hug,et al.  ADRIS – The Adverse Drug Reactions Information Scheme , 2004, Pharmacogenetics.

[25]  H. Hug,et al.  Ontology-based knowledge management of troglitazone-induced hepatotoxicity. , 2004, Drug discovery today.

[26]  Russ B. Altman,et al.  PharmGKB: the Pharmacogenetics Knowledge Base , 2002, Nucleic Acids Res..

[27]  Leland J. Gershell,et al.  A brief history of novel drug discovery technologies , 2003, Nature Reviews Drug Discovery.

[28]  Charlie Hodgman,et al.  An information-flow model of the pharmaceutical industry. , 2001, Drug discovery today.

[29]  Leroy Hood,et al.  The impact of systems approaches on biological problems in drug discovery , 2004, Nature Biotechnology.

[30]  Sally A. Hindle,et al.  The FlexX database docking environment--rational extraction of receptor based pharmacophores. , 2004, Current drug discovery technologies.

[31]  E. Jacoby,et al.  Chemogenomics: an emerging strategy for rapid target and drug discovery , 2004, Nature Reviews Genetics.

[32]  ariadne staff,et al.  The Information Grid , 2002 .

[33]  Tim Berners-Lee,et al.  Agent Technology on the Internet. 3. Integrating Applications on the Semantic Web. , 2002 .

[34]  Yan Huang,et al.  The software architecture of a distributed problem-solving environment , 2000, Concurr. Pract. Exp..

[35]  Olivier Bodenreider,et al.  Session Introduction , 2005, Pacific Symposium on Biocomputing.

[36]  Mario Cannataro,et al.  The knowledge grid , 2003, CACM.

[37]  Mario Cannataro,et al.  Proteus, a Grid based Problem Solving Environment for Bioinformatics: Architecture and Experiments , 2004 .

[38]  E. Kunkel Systems biology in drug discovery , 2004, Nature Biotechnology.

[39]  A. Verkman Drug discovery in academia. , 2004, American journal of physiology. Cell physiology.

[40]  Ian T. Foster,et al.  The data grid: Towards an architecture for the distributed management and analysis of large scientific datasets , 2000, J. Netw. Comput. Appl..

[41]  D. Gerhold,et al.  Better therapeutics through microarrays , 2002, Nature Genetics.

[42]  Thomas Lengauer,et al.  Novel technologies for virtual screening. , 2004, Drug discovery today.

[43]  Steven Tuecke,et al.  The Anatomy of the Grid , 2003 .

[44]  Steven Tuecke,et al.  The Physiology of the Grid An Open Grid Services Architecture for Distributed Systems Integration , 2002 .

[45]  J. Weinstein 'Omic' and hypothesis-driven research in the molecular pharmacology of cancer. , 2002, Current opinion in pharmacology.

[46]  Jonathan Knowles,et al.  A guide to drug discovery: Target selection in drug discovery , 2003, Nature Reviews Drug Discovery.

[47]  Philip Ball The speed of computers , 1999, Nature.

[48]  Mark Ellisman,et al.  e-Neuroscience: challenges and triumphs in integrating distributed data from molecules to brains , 2004, Nature Neuroscience.

[49]  Marco Roos,et al.  Future application of ontologies in e-Bioscience. , 2004 .

[50]  Robert Stevens,et al.  {myGrid} and the drug discovery process , 2004 .

[51]  Karen Schuchardt,et al.  Ecce—a problem‐solving environment's evolution toward Grid services and a Web architecture , 2002, Concurr. Comput. Pract. Exp..

[52]  P. Ball Physics at the Planck time , 1999, Nature.

[53]  E E Schadt,et al.  A new paradigm for drug discovery: integrating clinical, genetic, genomic and molecular phenotype data to identify drug targets. , 2003, Biochemical Society transactions.

[54]  Wang,et al.  Proteomics in drug discovery. , 1999, Drug discovery today.

[55]  Dalia Cohen,et al.  Functional genomics to new drug targets , 2004, Nature Reviews Drug Discovery.

[56]  C. Barnatt Office Space, Cyberspace and Virtual Organization , 1995 .

[57]  James A. Hendler,et al.  E-Science: The Grid and the Semantic Web , 2004, IEEE Intell. Syst..

[58]  J. M. Sauder,et al.  The promise of structural genomics in the discovery of new antimicrobial agents. , 2002, Current pharmaceutical design.

[59]  Carole Goble Carole Goble discusses the impact of semantic technologies on the life sciences , 2004 .

[60]  Lefkos Middleton,et al.  Disease-specific target selection: a critical first step down the right road. , 2005, Drug discovery today.