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Enabling Translational Medicine with BI (Technology Focus)

Published by: Datamonitor

Published: Mar. 27, 2007 - 14 Pages


Table of Contents


DATAMONITOR VIEW
CATALYST
SUMMARY
METHODOLOGY
ANALYSIS
Market pressures are driving pharmaceutical firms to embrace translational medicine
External forces are driving the adoption of translational medicine
Translational research requires BI technology components
Data integration is a key component of a data warehousing solution for R&D
Components of integration must support both spatial and temporal information
Data analytics tools must be built with domain expertise in order to derive knowledge from information
BI solutions must reflect domain expertise in the drug development process
Technology for translational medicine must support different types of end users
Four technology features add value to a BI solution for translational medicine
The pharmaceutical market requires usable technologies that empower users, without dictating a process
Technology must be flexible in scaling both up or down
In translational medicine, solutions need to integrate various data, software and hardware
Harvesting scientific knowledge within and across departments is a sign of a collaborative technology feature
ACTIONS
Align technology to R&D and clinical worflow challenges
Offer flexible solutions to fit the dynamic drug development process
Do not assume your end users are 'bi-lingual'
APPENDIX
Definitions
Abbreviations
External methodology
Further reading
Datamonitor Technology Consultancy
Ask the analyst


List of Figures


Figure 1: Technology aligned to translational medicine supports dynamic rather than linear models
Figure 2: Data integration includes ETL, data cleansing and refresh functions to support real-time exchange of diverse data
Figure 3: Data analytics with domain expertise enable decision support for translational research
Figure 4: Description of horizontal and vertical end-user titles
Figure 5: Technology feature components must align with different end users

Abstract

Introduction

The shift towards translational medicine depends on vendors offering technology solutions that are aligned to the unique needs of the pharmaceutical industry. BI tools, such as data analytics, must reflect domain expertise and encompass both research and development (R&D) and clinical departments of a pharmaceutical company.

Scope

  • Analyzes BI technology components, such as data integration and data analytics, for research and development in the pharmaceutical industry
  • Builds on ongoing primary research with pharmaceutical companies and technology vendors

    Highlights

    Market pressures are driving pharmaceutical firms to embrace translational medicine Translational research requires BI technology components BI solutions must reflect domain expertise for the drug development process; and Four technology features add value to a BI solution for translational medicine.

    Reasons to Purchase

  • Align your strategy with developments in the pharmaceutical industry
  • Understand the technology features important to pharmaceutical end users
  • Gain insight into BI applications for the early stages of drug development

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