Product Images Carbidopa And Levodopa

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 4 images provide visual information about the product associated with Carbidopa And Levodopa NDC 62332-333 by Alembic Pharmaceuticals 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 Tablets - carbidopalevo 25100mg

30 Tablets - carbidopalevo 25100mg

This text appears to provide instructions and dosage information for a medication containing both carbldopa and levodopa, with guidelines for dosage frequency, storage, and administration. The medication is supplied by Alembic Pharmaceuticals, and the text includes relevant identifying information such as the product NDC code.*

30 Tablets - carbidopalevo 50200mg

30 Tablets - carbidopalevo 50200mg

Each tablet of Carbidopa and Levodopa Extended-Release Tablets, USP contains 50mg Carbidopa (anhydrous equivalent, USP) and 200mg Levodopa (USP). The usual adult dosage should be taken as per the package insert. Tablets should be swallowed without chewing or crushing and should be stored at controlled room temperature. The medicine should be stored in a tightly closed container in a cool and dry place, protected from light and moisture. The medicine is manufactured by Alembic Pharmaceuticals Limited and is sold by Alembic Pharmaceuticals, Inc. The medicine is meant for prescription-use only and comes in a tightly dosed container of 30 tablets.*

Structure-Carbidopa - carbidopalevo carbi

Structure-Carbidopa - carbidopalevo carbi

Structure-Levodopa - carbidopalevo levo

Structure-Levodopa - carbidopalevo levo

The text seems to be a chemical formula or diagram. The formula consists of two molecules, OH and CHCHCOOH, separated by a vertical bar or a line. It also includes a chemical symbol NHz. As a standalone text, it holds no clear meaning or use.*

* 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.