Product Images Metronidazole
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 5 images provide visual information about the product associated with Metronidazole NDC 67296-0078 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.
metronidazole - 20220818125210 00001
This is a description of Metronidazole 500mg tablets, indicated for adults only. Each package contains 30 tablets with a lot number and expiration date for quality control. Instructions for dosage and storage conditions are provided. The manufacturer is Teva Czech Industries located in Czech Republic, and the distributor is Redpharm Drug in Eden Prairie, MN.*
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This is a description of Metronidazole 250 mg Tablets USP. Each tablet contains 250 mg of Metronidazole. The usual dosage instructions can be found in the package insert. It should be stored at 20° to 25°C (68° to 77°F) and protected from light. The medication should be kept out of reach of children. The tablets are manufactured in the Czech Republic by Teva Czech Industries and distributed by Teva Pharmaceuticals USA, Inc. The NDC number for the product is 50111-333-01 and the package contains 100 tablets.*
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This is a packaging label for Metronidazole Tablets USP, with each tablet containing 500 mg of metronidazole. The recommended storage condition is between 20°C to 25°C (68°F to 77°F), and it needs protection from light. The medication should be kept in a tight, light-resistant container with a child-resistant closure. The manufacturer is Teva Czech Industries in the Czech Republic, and the product is manufactured for Teva Pharmaceuticals USA, Inc. The NDC code for these tablets is 50111-334-01, and the package contains 100 tablets. It is advised to refer to the package insert for full prescribing information and dosage instructions.*
* 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.