Internet, probably the best source for speedier alerts on adverse drug reaction
Based on the FDA process to identify adverse drug reaction, much precious time and lives can be lost while the authorities are trying to build up the evidence for FDAs to act and issue a warning. The FDA method primarily relies on the public, doctors, and companies to report such event to the authorities. Hence, this process is extremely time consuming as it includes the legal reviews. This method also considers the occurrence and severity of the event, multiple discussions internal and externally before a warning is issued. Therefore, it has been receiving numerous criticisms by the public due to the lengthy process. So to improve this system, the FDA had announced the improved the post-marketing surveillance named Sentinel Initiative. Currently the investigators of Sentinel have created computer program to inspect over some 40 medical products or conditions.
However, fear not! In future, scientists could easily filter through the abundant data that was available in the internet to identify potentially serious adverse drug reactions. It is made possible by the algorithms formulas that are developed by researchers from University of Virginia and West Virginia University. These formulas could instruct computers to sift through tons of data from patient comments in online chats, websites and new stories to speedily enhance the detection of adverse drug reactions. Results have shown that it could identify potential adverse reaction faster than the federal regulators. The team has tested their formula by analyzing the web data on a sample of 20 drugs. In preliminary data, 80% of the results had shown that the formula was capable of identifying potential adverse event patterns three months earlier, while some years ahead of FDA’s official warnings. One major challenge the researchers are facing now is to sort through “noise”, the irrelevant information, while trying to identify constructive information such as getting cues from misleading sources.
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