The IBIL PV software will support drug safety business processes from an easy to-understand user interface and provide deep and integrated safety functionality with capability to scale to millions of cases and easily align with the available safety and business processes. Besides providing comprehensive visibility into reporting metrics and compliance, it will enable a highly scalable end-to-end safety process offering automated global case processing, periodic reporting, E2B intake and submission, as well as comprehensive reporting and detailed analytics.
We are uniquely poised to help global drug safety and PV organizations to perform better. We have made our solution unbeatable through deep domain understanding, detailed process knowledge and extensive industry experience. Drug Safety Team management can be highly effective with IBIL PV. You can experience your team more productive than ever – highly flexible workflows, tracking and notification mechanisms improve team productivity.
We cover the latest technologies that are in trend to provide our customers the best of valuable service
Electronic medical records and research documents capture large quantities of clinically significant information. However, much of this information is often in a form that is not amenable to analysis because of its free-text, unstructured nature. Our NLP solution – IBIL-IntelliCP built on UIMA framework transform this information into structured data for use in quality improvement, research, population health surveillance, and decision support.
IBIL-IntelliCP evolved out of the necessity to scale-up the existing framework to customize and tune techniques that fit a variety of tasks, including document classification, tuned concept extraction for specific conditions, patient classification, and information retrieval related to the patient, history, disease manifestation, details of laboratory tests, prescribed interventions, and outcomes and much more.
As part of the solution, we have implemented several informatics tools to leverage clinical data for research:
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