Product Images Ketamine Hydrochloride

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 4 images provide visual information about the product associated with Ketamine Hydrochloride NDC 71872-7258 by Medical Purchasing Solutions, Llc, 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.

71872-7258-01.PDP - 71872 7258 01

71872-7258-01.PDP - 71872 7258 01

Ketamine HCI Injection is a concentrate solution for intramuscular or slow intravenous use, with a usual dosage as per package insert. It comes in a 5 mL multi-dose vial with a strength of 500 mg/5 mL (100 mg/mL) and contains ketamine hydrochloride equivalent to 100 mg of ketamine. It also includes benzethonium chloride as a preservative. The solution's color may vary from colorless to slightly yellowish and darken over time, but it does not affect its potency. The product should be protected from light and kept out of children's reach. It is manufactured by Hikma Farmaceutica (Portugal), S.A., and distributed by West-ward Eatontown, NJ 07724 USA, while the repackaged version is distributed by Medical Purchasing Solutions in Scottsdale, AZ 85260.*

structure - ketamine hydrochloride injection usp 1

structure - ketamine hydrochloride injection usp 1

PLB936 - ketamine hydrochloride injection usp 2

PLB936 - ketamine hydrochloride injection usp 2

serialization image sample - ketamine hydrochloride injection usp 6

serialization image sample - ketamine hydrochloride injection usp 6

This text contains product identification information commonly used in retail and manufacturing settings. It includes a Global Trade Item Number (GTIN), a Serial Number (SN), an expiration date (EXP) formatted as MMMYYYY, and a Lot number (LOT). This data is used to track and manage inventory, expiration dates, and prevent counterfeiting.*

* 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.