Hydrocodone Bitartrate And Acetaminophen Tablet
Product Images NDC 82804-003
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Product Visual Gallery
This gallery contains 3 technical images submitted to the FDA as part of the official labeling for Hydrocodone Bitartrate And Acetaminophen (NDC 82804-003). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.
As provided by Proficient Rx Lp, these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.
Chemical Structure Of Acetaminophen (Hydrocodone Bitartrate And Acetaminophen Tablet 2)
Acetaminophen, also known as Paracetamol, is a commonly used over-the-counter medication for pain relief and fever reduction. Its chemical formula is CHgNO, and it has a molecular weight of 151.16. Acetaminophen is often used to alleviate headaches, muscle aches, backaches, toothaches, and the symptoms of colds and flu. It is generally safe when taken as directed, but it is important to follow the recommended dosage and to avoid exceeding the maximum daily limit to avoid potential liver damage. Always consult a healthcare professional before taking any medications.*
82804-003-30 (Hydrocodone Bitartrate And Acetaminophen Tablet 5)
This text appears to be a description of a medication package containing Hydrocodone / APAP tablets. The package is labeled with the NDC number 82804-003-30 and was packaged by Proficient Rx LP. It is intended for prescription use only and is accompanied by a Medication Guide for each patient. The package includes 30 tablets, each containing 10mg of Hydrocodone Bitartrate USP and 325mg of Acetaminophen USP. The tablets are white and capsule-shaped, with the imprint "M367" on one side and a bisect line on the other. The lot number is 00000 and the serial number is MASTER. The package should be stored at a temperature between 20°C-25°C (68°F-77°F).*
* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.