A post by Egon on Biospider got me thinking a little. There is a trend in the life science industry to look at scientific information in some of the same ways as enterprises have historically looked at business intelligence. A quick search for the term “business intelligence” will give you solutions from Microsoft, Oracle, SAS, etc. The goal of business intelligence is to help your make decisions faster and more efficiently. The data being collected by an enterprise are a valuable source of knowledge and using large data warehouses and complex analytics, companies have made a killing in this field.
Via Lijit, I found this post by Joerg where he defines Business Intelligence. Now read that definition and think about the role of informatics in a drug development environment.
If you are in the business of developing drugs, the information available about the drug, ranging from bioinformatics, clinical information, lab notebooks, etc, all constitute knowledge pertaining to successful approval and post-marketing success of the drug. This could further include financial metrics, and any other numbers that could help you make decisions about a drug program. Pharma companies today apply BI solutions, especially to make market decisions and go/no-go decisions. However, I wonder what data they use? And I wonder if this is a one time decision making process or something that happens on a continual basis (All of Jeff Jonas’ theories on Perpetual Analytics apply here)?
I believe there will be a time when life science companies will begin looking at biological, chemical, etc information as a core enterprise asset, rather than something for the research crowd. Why is that significant? A constant irritation as someone in the scientific software world, and I suspect this holds true for those in drug discovery groups, is the difference in the budget for enterprise intelligence software vs. software for molecular modeling and informatics. Perhaps that is why companies like Accelrys (my previous employer) are positioning themselves as “intelligence” companies. However, the change is cultural and positioning changes only go so far.
Scientific intelligence is business intelligence
A post by Egon on Biospider got me thinking a little. There is a trend in the life science industry to look at scientific information in some of the same ways as enterprises have historically looked at business intelligence. A quick search for the term “business intelligence” will give you solutions from Microsoft, Oracle, SAS, etc. The goal of business intelligence is to help your make decisions faster and more efficiently. The data being collected by an enterprise are a valuable source of knowledge and using large data warehouses and complex analytics, companies have made a killing in this field.
Via Lijit, I found this post by Joerg where he defines Business Intelligence. Now read that definition and think about the role of informatics in a drug development environment.
If you are in the business of developing drugs, the information available about the drug, ranging from bioinformatics, clinical information, lab notebooks, etc, all constitute knowledge pertaining to successful approval and post-marketing success of the drug. This could further include financial metrics, and any other numbers that could help you make decisions about a drug program. Pharma companies today apply BI solutions, especially to make market decisions and go/no-go decisions. However, I wonder what data they use? And I wonder if this is a one time decision making process or something that happens on a continual basis (All of Jeff Jonas’ theories on Perpetual Analytics apply here)?
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I believe there will be a time when life science companies will begin looking at biological, chemical, etc information as a core enterprise asset, rather than something for the research crowd. Why is that significant? A constant irritation as someone in the scientific software world, and I suspect this holds true for those in drug discovery groups, is the difference in the budget for enterprise intelligence software vs. software for molecular modeling and informatics. Perhaps that is why companies like Accelrys (my previous employer) are positioning themselves as “intelligence” companies. However, the change is cultural and positioning changes only go so far.
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