Product Images Nifedipine ER

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 4 images provide visual information about the product associated with Nifedipine ER NDC 50268-598 by Avpak, 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 - 597 15 30mg

30 - 597 15 30mg

This is a description of a medication package for NIFEdipine extended-release tablets. The tablets are for prescription use only and come in a pack of 50 unit-dose tablets. The dosage of each tablet is 33 mg of NIFEdipine. The package includes instructions for use and storage. The medication should be kept at a controlled room temperature and protected from moisture and light. It should also be kept out of reach of children. The tablets are manufactured by Akire and distributed by Avkare.*

60 - 598 15 60mg

60 - 598 15 60mg

This is a medication with 50 extended-release tablets of NIFEdipine, USP, in a unit dose package. The tablets are meant for oral use only and each has 6 mg of NIFEdipine. The recommended dosage instructions must be found in the inserted documentation or package prescribing. It is important to store the product between 20°-25°C (66°-77°F) and protect it from moisture, humidity, and light. The manufacturer is AVKARE. No further information is available.*

90 - 599 15 90mg

90 - 599 15 90mg

This is a prescription drug with the NDC 50268-599-15. It contains NIFEdipine and is available in extended-release tablets, USP. Each unit dose contains 5x10 tablets. The dosage should be followed according to the prescribing package and the tablets should be stored at a temperature between 20°C-25°C. The drug should be kept away from children. The drug is manufactured by Avkare, and the expiry date is March 2019.*

Structural Formula - Structural Formula

Structural Formula - Structural Formula

* 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.