Maximum Strength Mucus Relief Dm Tablet, Extended Release
Product Images NDC 49035-956

Product Visual Gallery

This gallery contains 2 technical images submitted to the FDA as part of the official labeling for Maximum Strength Mucus Relief Dm (NDC 49035-956). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.

As provided by Wal-mart Stores, Inc., these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.

FDA Label Image

Package Label-principal Display Panel (1200 mg/60 mg (14 Tablet Carton Label))

The Equate Mucus Relief DM Extended-Release Tablets contain Guaifenesin and Dextromethorphan Hydrobromide to relieve cough and reduce phlegm. They are intended for adults and children who are 12 years and older. The recommended dose is one tablet every 12 hours, and not more than two tablets in 24 hours. The tablets should not be crushed, chewed, or broken and should be taken with a full glass of water. It is not available whether the tablets are gluten-free or not. The product information also includes warnings, directions, and other information that should be considered before using.*

FDA Label Image

Package Label-principal Display Panel (1200 mg/60 mg (14 Tablet bottle))

This is a drug product called "Mucus Relief" which is an expectorant/cough suppressant. It helps to relieve cough due to minor throat and bronchial irritation as might occur with the common cold or inhaled irritants. Each extended-release tablet contains Dextromethorphan Hycdrobromide USP 60 mg (cough suppressant) and Guaifenesin USP 1200 g (expectorant). The drug should be taken as per the directions noted on the package. The product is distributed by Walmart Inc. and originated from India. For questions or comments, customers can call the number 1-888-287-1915.*

* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.