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This paper presents a proposed methodology to extract strong association rules by frequently occurring inactive ingredient combinations using the concept of Association Rule Mining which will help identify the inactive ingredient contributing the most to popularity levels and rating of the medicines available in market, assisting in curating better marketable and effective medicines and also assist in reducing unnecessary inactive ingredients to be excluded in formulation.

Association Rule Mining of Inactive Ingredients in Drugs