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Big Data and Proactive Pharmacovigilance

Posted on September 20th, 2017 by in Pharmacovigilance

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Traditionally thought of as a post-market process, pharmacovigilance is how pharmaceutical companies monitor and address any safety issues that arise once a drug becomes available commercially. However, some companies are now thinking ahead about these potential safety concerns with what is known as “proactive PV”. The proactive approach means that researchers start trying to identify possible drug-drug interactions (DDIs) during every stage of the drug discovery and development process, therefore opening up the possibility of solving a problem before it actually becomes one.

So how can these potential DDIs be detected so early in the drug development process? Well, big data is certainly a big help. Comprehensive in silico systems, text mining and other technologies can be adopted by companies to enable them to get the most out of the available data. But the reality is that the data sources themselves can be hard to wrangle. There aren’t universal standards for input or analysis, and the systems being used vary from one organization to another.

Furthermore, it’s important to consider that there are other valuable types of data that you may not even be factored in yet. In the case of DDI interactions, for instance, it’s not just about how drugs interact with one another, but how a drug interacts with a patient’s food or with herbal medicines they may be using. Real-world data and evidence, much of which comes from EHRs, is also critical to consider.

Read the article How Pharma CIOs Can Use Big Data Techniques to Improve Drug Safety to learn more.


All opinions shared in this post are the author’s own.

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