Life Sciences Informatics From Data to Drugs

Data collection, storage, analysis, and sharing are critical tasks in drug discovery and development companies. This report navigates the rapidly-evolving landscape of bioinformatics technologies, and assesses which ones are key to productivity and success. 

This Report Analyzes the Following Key Trends:

How pharmaceutical companies are spending their IT budgets.

Ways in which life science companies are leveraging the information they have through systems biology (i.e., pathways and network analysis) and/or knowledge management.

How bioinformatics technologies may address key unmet needs in proteomics.

The future role of, and potential market for, bioinformatics in genomics-driven or -enabled drug discovery and development companies.

Overview: 

Informatics are essential at every step of genomics-based drug discovery and development. However, over the last couple of years, the commercial landscape of life sciences information technology has changed dramatically. The field of bioinformatics, in particular, has gone through a dramatic boom/bust. At the same time, a large number of IT companies are looking to the drug discovery and development arena as a new market opportunity. Pharmaceutical companies, meanwhile, are faced with rising pressure to reduce or at least control costs, and have a growing need for new informatics tools to help manage the influx of data from genomics, and turn that data into tomorrow's drugs. 

Life Sciences Informatics: From Data to Drugs is a new Cambridge Healthtech Institute (CHI) Life Science report that examines the overall landscape of bioinformatics and highlights those approaches, and companies pursuing them, that will likely address the indus-try's evolving needs. Key IT tools, such as high-performance computing, Web services, and grids, that are being used to improve the speed and efficiency of drug discovery and development are also discussed. 

It's now clear that selling bioinformatics data and/or software is a tricky business model. Furthermore, true breakthroughs are still lacking, particularly in key areas such as gene prediction, data mining, protein structure modeling and prediction, and modeling of complex biological systems. However, most experts agree that IT and bioinformatics are essential to reaching the improved productivity the pharmaceutical industry craves. The problem is not the quality of the software and hardware-rather, the difficulty lies in bringing the new laboratory tools to full maturity, teaching biologists how to manage high-throughput experiments and the data they generate, and sharing and integrating all this data in a meaningful way. The ultimate goal is to take the data from all these types of studies and to generate detailed models of complex systems, particularly biological pathways. Life Sciences Informatics: From Data to Drugs is crucial reading for companies seeking to reach that goal. 

Thought Leaders Interviewed for This Report:

Howard Asher, Sun Microsystems, Inc.; Jeffrey Augen, TurboWorx; Dejan Bojanic, Millennium Pharmaceuticals; Geoffrey Duyk, Exelixis; Jack Elands, IDBS Ltd.; David Finkelstein, Affymetrix; Nat Goodman, Institute for Systems Biology; Andrew Grimshaw, Avaki; John Helfrich, NuGenesis; Roberta Katz, EMC Corporation; Carol Kovak, IBM; Eric Meyers and Jack Pollard, 3rd Millennium; Alan Roter, Iconix Pharmaceuticals; Yury Rozenman, formerly of Platform Computing (now with IBM Life Sciences); Mick Savage, Consultant; Shiv Tasker, formerly of Blackstone Computing (now with Tribiosys); Bernard P. Wess, Jr., PERSEID Software Ltd. 

Publication date/length: April 2003, 188 pages.

Publisher: Cambridge Healthtech Institute 

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