Method and System for automatically detecting compatibility of Food, Supplements, and Over-the-Counter Medicines with Prescription Drugs
Publication Date: 2016-Aug-18
The IP.com Prior Art Database
Disclosed is a method and system for automatically detecting compatibility of food, supplements, and over-the-Counter Medicines with Prescription Drugs
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Method and System for automatically detecting compatibility of Food , Supplements, and Over-the-Counter Medicines with Prescription Drugs
With increased use of drugs (prescription and non-prescription), specialized diets, supplements, as well as herbal medications, it has become very hard to know and to find out how the composition of these components may interact with each other and produce harmful or unintended side effects (such as allergic reactions).
Studies and Research in the food and drug industry has been trying to address issues like this but is often limited to a certain drugs or components that the studies are focused on. With the rapid growth of the use of supplements and the use of alternative medicines and specialized diets which are mostly unregulated, there is growing risk of dangerous side-effects that are very hard to detect or check on. In addition, professional research and studies also often overlook the use of home remedies which are passed on from generation to generation and may be traced back to hundreds or even thousands of years of history.
There is therefore a need for a method and system for automatically detecting patterns of drug interactions.
The method and system as illustrated in the figure, continuously crawl and collect real time data from multiple data sources (official and non-official, structured and unstructured) to automatically detect patterns of drug interactions using cognitive technology. The method and system also combines information from the food and drug industries and government organizations (e.g. FDA, manufacturer's documentation, medical journals and professional publications), with the vast amount of information exist on the web (crowd-sourced data) such as social media, user/product reviews, forums and blogs. The information ca...