Product Images Esomeprazole Magnesium

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 6 images provide visual information about the product associated with Esomeprazole Magnesium NDC 68071-4886 by Nucare 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.

PDP - 68071 4886 3

PDP - 68071 4886 3

This is a description of pharmaceutical products manufactured by NuCare Pharmaceuticals, Inc. The product is Esomeprazole Magnesium in capsule form with a strength of 40mg. The product comes in a 30 count bottle, with lot number 000000, and an expiration date of 00-00. The National Drug Code (NDC) for this product is 68071-4886-03. Patients are advised to contact their medical doctor for any medical advice or adverse reactions. It is essential to keep the product out of children's reach, and the storage temperature is recommended to be between 59-86°F.*

Esomeprazole-1 - Esomeprazole 1

Esomeprazole-1 - Esomeprazole 1

This appears to be a figure referring to a study (177) that compares the maintenance of healing rates by month among four different groups (N=52, N=98, N=91, n=94). The groups are labelled as "Eousaie 20 mg", "Esomeczole 20 mg", "Eamcpde 10 mg", and "Placebo", respectively. There is not enough information to provide further context or interpretation.*

Esomeprazole-pic-2 - Esomeprazole pic 2

Esomeprazole-pic-2 - Esomeprazole pic 2

Esomeprazole-pic-3 - Esomeprazole pic 3

Esomeprazole-pic-3 - Esomeprazole pic 3

The image shows a graphic representation of the percentage of patients who were free of heartburn symptoms on each day of study 225. No further information is available.*

Esomeprazole-pic-4 - Esomeprazole pic 4

Esomeprazole-pic-4 - Esomeprazole pic 4

Esomeprazole-str-1 - Esomeprazole str 1

Esomeprazole-str-1 - Esomeprazole str 1

* 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.