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Life Sciences Increased Demands for More Data, More of the 'Right' Data

By Luke Hager
March 31, 2011

While 2011 looks to be a challenging year for the U.S. economy and for life sciences, there is real potential to turn chaos into opportunity. This article outlines our view of the major trend in life sciences for 2011 in terms of business intelligence (BI). For starters, business intelligence (BI) are processes embedded within applications that build on existing data warehouses and provide analytical processing tools that allow users to more effectively analyze such data. BI enables organizations to more rapidly develop existing and new analyses and reports for improved decision-making power and information dissemination capacity.


What first comes to mind when we think of the concept of “business intelligence” or “BI” are the typical mogul giants such as Microsoft, Oracle, and SAS.  All of which offer more enterprise wide BI and are not specifically tailored to any one specific vertical. Overall the general goal of business intelligence is to help organizations to make decisions faster and more efficiently. The data being collected by an enterprise is a valuable source of knowledge and using large data warehouses and complex analytics, the moguls have made a killing in this field.  

The Life Science Climate is Changing

What is interesting to note in today’s changing climate is that there does seem to be a paradigm shift in the way we now value scientific information, which is in the same way as enterprises have traditionally looked at business intelligence. Life Sciences companies today must monitor their process performance at every level, identify areas of improvement, continuously optimize them and report proof of compliance to appropriate regulatory authorities. Organizations are beginning to comprehend the value scientific business intelligence solutions.  They will increasing  play a key role in business performance improvement. There is quite a bit of interest in scientific business intelligence software for the integration, mining, analysis, modeling and simulation, management and interactive reporting of scientific data. 

Being able to rely on a data sources’ validity, quality and relative immediacy are concerns for biotechnology, pharmaceutical and life sciences companies. ThotWave Technologies, a Business Intelligence consultancy serving the scientific community, is providing solutions to help organizations manage, analyze and extract maximum value from their scientific data. ThotWave also helps maximize a return on investment and improve the overall quality of decision-making support throughout an organization by making data more predictive, simple to access, and easy to use and understand.  

Another company serving the scientific community with a business intelligence platform is Accelrys. Accelrys offers a vast portfolio of computer-aided design modeling and simulation offerings which assist scientific and research-based organizations in conducting scientific experiments 'in silico' in order to reduce the duration and cost of discovering and developing new drugs and materials. The company touts it’s flexibility, ease-of-use and advanced chemical, text and image analysis and reporting capabilities to enable the mining, aggregating, analyzing and reporting of scientific data from disparate sources.

Empowering decisions in today's tough pharmaceuticals market is Information Builders, an business intelligence software provider that also provides integration services. Information Builders sees the life science community struggling with shortened business cycles, faster information flow, new marketing channels, risky product development cycles and approvals, emerging generic and biotechnology competition, ever-accelerating discoveries, more limited influencer mind share, and continuation of the merger and acquisition trends in today’s economic climate. 

The Bottom Line

By generating valuable scientific information from multiple sources, companies can increase their competitive edge, provide better service, streamline operations and make better business decisions for increased profits. Extracting business intelligence from scientific data can enable companies to quickly sort through large amounts of data and use that data to detect trends and patterns. It also provides companies with effective analytical modeling tools that more accurately predict the financial impact of future actions than manually generated projections.


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