Product Images Meloxicam
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Product Label Images
The following 4 images provide visual information about the product associated with Meloxicam NDC 67296-1817 by Redpharm Drug, Inc., such as packaging, labeling, and the appearance of the drug itself. This resource could be helpful for medical professionals, pharmacists, and patients seeking to verify medication information and ensure they have the correct product.
30 COUNT - 67296 1817 3
This is a prescription medication called Meloxicam, which comes in the strength of 7.5mg in a bottle of 30 tablets. The usual adult dosage is specified in the package insert. The medication has been manufactured by Cadila Healthcare LTD in India and distributed by Redpharm Drug in Eden Prairie, MN. The National Drug Code of this medication is 67296-1817-3 and it has a lot number of 904518X1. The medication should be stored at a controlled room temperature and the expiry date is mentioned as 09/21.*
structured product formula for meloxicam - 86b423ad 7aab 4d96 83bf a259a61f8a9b 01
Meloxicam Tablets, 7.5 mg - 86b423ad 7aab 4d96 83bf a259a61f8a9b 02
This is a package for Meloxicam Tablets, USP with 500 tablets, each containing Meloxicam, USP 7.5 mg, meant for Rx only, and with usual dosage described in the package insert. It should be stored at 20° to 26°C and kept in a dry place. The package should be dispensed in a tight container and kept out of the reach of children. The code number is HPI72104. The product is manufactured by Cala Healthcare Ltd, India, and distributed by Zydus Pharmaceuticals (USA) Inc., Pennington, NJ 08534.*
Meloxicam Tablets, 15 mg - 86b423ad 7aab 4d96 83bf a259a61f8a9b 03
Each tablet of this drug contains Meloxicam, and complete prescribing information is available in the package insert. The recommended storage temperature is between 20°C and 26°C. The drug should be kept out of the reach of children. The manufacturer of this medicine is Cadia Healthcare Ltd in India. Unfortunately, the text is incomplete and does not provide further details.*
* The product label images have been analyzed using a combination of traditional computing and machine learning techniques. It should be noted that the descriptions provided may not be entirely accurate as they are experimental in nature. Use the information in this page at your own discretion and risk.