title: Effective knowledge management in translational medicine.
abstract: BACKGROUND
  The growing consensus that most valuable data source for biomedical discoveries is derived from human samples is clearly reflected in the growing number of translational medicine and translational sciences departments across pharma as well as academic and government supported initiatives such as Clinical and Translational Science Awards (CTSA) in the US and the Seventh Framework Programme (FP7) of EU with emphasis on translating research for human health.
  
  
  METHODS
  The pharmaceutical companies of Johnson and Johnson have established translational and biomarker departments and implemented an effective knowledge management framework including building a data warehouse and the associated data mining applications. The implemented resource is built from open source systems such as i2b2 and GenePattern.
  
  
  RESULTS
  The system has been deployed across multiple therapeutic areas within the pharmaceutical companies of Johnson and Johnsons and being used actively to integrate and mine internal and public data to support drug discovery and development decisions such as indication selection and trial design in a translational medicine setting. Our results show that the established system allows scientist to quickly re-validate hypotheses or generate new ones with the use of an intuitive graphical interface.
  
  
  CONCLUSIONS
  The implemented resource can serve as the basis of precompetitive sharing and mining of studies involving samples from human subjects thus enhancing our understanding of human biology and pathophysiology and ultimately leading to more effective treatment of diseases which represent unmet medical needs.
authors.affiliation: Centocor R&D, Inc, 3210 Merryfield Row, San Diego, CA 92130, USA. sszalma@its.jnj.com
authors.forename: Sándor
authors.initials: S
authors.lastname: Szalma
authors.forename: Venkata
authors.initials: V
authors.lastname: Koka
authors.forename: Tatiana
authors.initials: T
authors.lastname: Khasanova
authors.forename: Eric D
authors.initials: ED
authors.lastname: Perakslis
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D019451:Information Management; D015201:Meta-Analysis as Topic; D008954:Models, Biological; D009369:Neoplasms / Q000235:genetics / Q000473:pathology; D015203:Reproducibility of Results; D057386:Search Engine; D012984:Software; D057170:Translational Research, Biomedical / Q000458:organization & administration*
chemical_list: D014408:Biomarkers, Tumor