Product Images Carbamazepine
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 5 images provide visual information about the product associated with Carbamazepine NDC 60687-583 by American Health Packaging, 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.
200 mg Carbamazepine ER Tablet Blister - 200 mg Blister
Carbamazepine is a medication used to treat epilepsy and neuropathic pain. The provided text is not-readable and appears to be a mix of errors and random characters.*
200 mg Carbamazepine ER Tablets Carton - 200 mg Carton
This is a description of Carbamazepine Extended-Release Tablets, USP in a packaging of 30 tablets (3 x 10) with NDC 60687-583-21 and Rx Only label for the usual prescription. Each tablet contains Garbamazepine USP 200mg to be swallowed whole and never crushed or chewed. It is recommended to store between 20-25°C and protect from moisture. The accompanying Medication Guide is to be dispensed by the pharmacist to each patient, and the drug product is distributed by American Hodih Packaging in Columbus, Ohio.*
400 mg Carbamazepine ER Tablet Blister - 400 mg Blister
400 mg Carbamazepine ER Tablets Carton - 400 mg Carton
Carbamazepine Extended-Release Tablets are a prescription medicine with 400mg Carbamazepine USP per tablet. It is advised to be swallowed whole and never chewed or crushed. The package contains 30 tablets, with the usual dosage specified on the package insert. It is recommended to store the tablets at 20° to 25°C (68° to 77°F), and protect from moisture. This medication should be kept out of reach of children. The package should not be used if the blister is torn or broken. The drug product in this package is from NDG' 16571-682, produced by Rising Pharma Holdings, Inc. and distributed by American Health Packaging in Columbus, Ohio 43217.*
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* 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.