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November 17, 2009
Is your company's process of collecting and analyzing clinical trial study data too manual and time consuming?
Clinical trials play an important role in medical research to answer specific questions about vaccines or new therapies or new ways of using known treatments. They are being conducted to determine whether new drugs or treatments are both safe and effective and are seen as being the fastest and safest way to find treatments that work in people. It is therefore critical for pharmaceutical companies and their partners to be able to efficiently collect and analyze the data resulting from various trial phases as well as data collected from similar studies. Moreover, companies need to be able to integrate this data with detailed patient data to minimize the drug's risks and optimize its usage as well as its commercial success.
Having worked with several prospective customers in this space, it is astonishing to us that the process of collecting data from clinical trials and related studies remains very labor-intensive and time consuming even so the likes of Informatica have been selling into this market for years. What we see is that most companies are still relying on home-grown and sub-optimal vendor ETL solutions to integrate clinical study and patient data from a variety of sources for reporting and analysis purposes. Due to architectural limitations, converting source data in XML documents and other complex data formats remains a daunting task for today's ETL tools. Users tell us that the mapping process of the XML from sources to targets and delivering the application take an unacceptable amount of time. They also say that the data mappings are very brittle, making it difficult to easily incorporate additional clinical data sources and to reuse mapping rules within or across different mapping projects. And ask them, if they are satisfied with the XML data processing performance of their incumbent ETL tool!
Unlike other ETL and data integration tools, we have demonstrated to several clients over the past year that our innovative semantic data integration system is well suited to overcome many of data integration challenges they face. We have shown in a number of proof of concepts that our parallel data processing engine can process the even most demanding XML documents at impressive speed. Adding new data sources can be done quickly with our smart semantics approach. And expressor allows them to seamlessly integrate their existing operational systems and databases.
Michael Waclawiczek
VP, Marketing and Product Management
Posted by expressor software at November 17, 2009 8:15 AM
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