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Signs of Life in Life Sciences IT Spending

By Alan S. Louie

Nov. 15, 2006 | Back in 2002, when Bio-IT World was launched, our predecessors at IDC predicted that IT spending in the life sciences would grow dramatically from around $12.2 billion in 2001 to a projected $30 billion in 2006*. Despite the apparent difficulties that the IT infrastructure sector has faced during those years, it may surprise many readers that we believe these prior estimates were spot on. Based on IDC’s Health Industry Insights’ most recent quarterly survey on Life Science industry spending (3Q06), we project that $29.7 billion will be spent globally in 2006 to support IT infrastructure in life sciences.

With a compound annual growth rate (CAGR) of 19.9 percent, this sustained increase has been truly impressive. Despite concerns that future spending would likely be deferred to allow time to absorb recent acquisitions, spending has continued at a rapid pace. We currently project a 6.5 percent average growth rate moving forward, although new indicators of industry sentiment suggest that IT spending growth may truly be beginning to slow, primarily due to near term major industry cost cutting efforts. 

Despite the impressive overall growth, IT spending is uneven at best, with negative growth in some areas (e.g. high-end server spending, -0.3% CAGR) and high growth in others (e.g. networking equipment, +11.5% CAGR). In looking at areas of combined high spending and high growth (see Table), new IT infrastructure investments seem to be focused around connectivity, integration of currently available data resources, and improving utilization of data across traditional organizational boundaries.

Pharmaceutical and other life science companies are confronting explosive growth in the volume of data being generated from R&D programs including high-throughput discovery instrumentation, molecular imaging (pre-clinical and clinical), and access to external data sources (e.g. human and other genome sequences). Having the data is one thing, but effectively using the data is considerably more difficult.

As a first step, life science companies are actively consolidating disparate data resources into common data warehouses. IT infrastructure spending directly supports investments in these efforts. But this must be considered as merely the initial steps on a path towards development of an institutional knowledge resource. The move beyond common data repositories is considerably more complex and will require fundamental changes to current practices across the organization. To begin the transition from data to knowledge, organizations must fully recognize the value of data as a resource and especially recognize the value of the information obtained from failed experiments.

A number of commercial software vendors, e.g. Elsevier MDL, InforSense, and Ingenuity, offer enterprise solutions that promise full access and connectivity between a company’s diverse datasets, enabling direct cost savings and increased productivity. Whether its streamlining accessibility of instrument-generated data to advanced analytical applications, seamless pipelining of data between applications, or plug-and-play access to content-rich proprietary data and knowledge resources, these software solutions should be considered primarily as supporting capabilities that life science companies draw upon to enhance their research efforts. New IT infrastructure investments in this applications area need to bring clear new capabilities (and not just incremental improvements) to deliver value for both the near and long term. 

The development of an effective knowledge resource will require knowledgeable bioinformatics experts, an extensible IT infrastructure, a powerful and highly user friendly user interface, massive data content, and complex informatics solutions that enable aggregation, analysis, and predictive modeling. Together, this resource should enable effective knowledge-on-demand relative to a broad variety of research-specific questions, related insights based on prior experiences and results, activity predictions based on similar efforts, and clear identification of knowledge gaps. This solution is attainable in the near term, but must be designed to grow in unspecified directions, based on the expectation of new scientific discoveries, advances in technology platforms, and the ever growing pool of data.

Alan S. Louie, Ph.D., is research director for Health Industry Insights, an IDC company. Email:

*Worldwide Bio-IT Infrastructure Forecast and Analysis, 2002-2006 — IDC #28724.

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