Product Images Esomeprazole Magnesium

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Product Label Images

The following 6 images provide visual information about the product associated with Esomeprazole Magnesium NDC 68071-5074 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 5074 6

PDP - 68071 5074 6

This is a description for NuCare Pharmaceuticals' Esomeprazole Magnesium 20mg D-R Capsules used to relieve the symptoms of gastroesophageal reflux disease (GERD) such as heartburn. This medication has a National Drug Code (NDC) of 68071-5074-6 and a Manufacturer NDC of 62175-820-46. Each capsule contains 20mg of Esomeprazole Magnesium as the active ingredient. The bottle has a lot number of 000000 and comes in an opaque dark blue and opaque white capsule. This drug should be taken according to the prescription of a doctor, and it is necessary to keep it away from children. The recommended storage temperature for the drug is between 59°F to 86°F.*

Figure 1 - esomeprazole magnesium delayed release capsules us 1

Figure 1 - esomeprazole magnesium delayed release capsules us 1

Figure 2: Maintenance of Healing Rates by Month (Study 177) - esomeprazole magnesium delayed release capsules us 2

Figure 2: Maintenance of Healing Rates by Month (Study 177) - esomeprazole magnesium delayed release capsules us 2

Figure 3: Maintenance of Healing Rates by Month (Study 178) - esomeprazole magnesium delayed release capsules us 3

Figure 3: Maintenance of Healing Rates by Month (Study 178) - esomeprazole magnesium delayed release capsules us 3

Figure 4 - esomeprazole magnesium delayed release capsules us 4

Figure 4 - esomeprazole magnesium delayed release capsules us 4

Figure 5 - esomeprazole magnesium delayed release capsules us 5

Figure 5 - esomeprazole magnesium delayed release capsules us 5

* 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.