Product Images Phentermine Resin ER

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 2 images provide visual information about the product associated with Phentermine Resin ER NDC 0527-1398 by Lannett Company, 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.

phentermine-resin-cap-15mg - phentermine resin capsules 1

phentermine-resin-cap-15mg - phentermine resin capsules 1

This text provides information related to the usual dosage, storage instructions, and packaging details for Phentermine Resin Extended-Release Capsules. The package insert should be consulted for full prescribing information. The medication should be kept in a tightly closed container with a child-resistant closure and stored at a controlled room temperature. The capsules contain Phentermine and other inactive ingredients. The manufacturer is Lannett Company, Inc. Lot number and expiration date are also provided.*

phentermine-resin-capsule-30mg - phentermine resin capsules 2

phentermine-resin-capsule-30mg - phentermine resin capsules 2

This is a prescription medicine with NDC 0527-1366-01. It is an extended-release capsule that contains cationic resin complex equivalent to 30mg phenferrmina base. Inactive ingredients include Dibasic Calcium Phosphate, Talc, Calcium Carbonate, Gelatin, Ethanol, Black Iron Oxide, N-Butyl Alcohol, Propylene Glycol, FD&C Blue #2 Aluminum Lake, FD&C Red #40 Aluminum Lake, FD&C Blue #1 Aluminum Lake, D&C Yellow #10 Aluminum Lake, Ethanol, and Methanol. Recommended storage is at 20° to 25°C (68° to 77° F) in a tightly closed container as defined in the USP with Controlled Room Temperature. The medicine bottle is sealed and contains 100 capsules. It is manufactured by Lannett Company, Inc. and made in the USA. Lot number and expiration date are also available.*

* 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.