Product Images Dexlansoprazole Delayed Release

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Product Label Images

The following 4 images provide visual information about the product associated with Dexlansoprazole Delayed Release NDC 51407-746 by Golden State Medical Supply, 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.

51407-746-30.jpg - 51407 746 30

51407-746-30.jpg - 51407 746 30

This is a prescription drug with the NDC code 51407-746-30 in the form of delayed-release capsules, containing 30mg of Dexlansoprazole as enteric-coated granules. The medication guide should be printed from https://gsms.us/ and given to patients by the pharmacist. The recommended dosage should be obtained from the accompanying prescribing information. The capsules should be stored in a light-resistant, tightly sealed container between 20°C to 25°C (68°F to 77°F) and kept out of the reach of children. The manufacturer is GSMS, Incorporated, and this information is revised as of 03/23.*

51407-747-30.jpg - 51407 747 30

51407-747-30.jpg - 51407 747 30

This is a medication called Dexlansoprazole available in the form of Delayed-Release Capsules. Each capsule contains 60 mg of Dexlansoprazole. The medication guide needs to be dispensed to each patient by the pharmacist. The dosage needs to be determined as per the accompanying Prescribing Information. It needs to be stored in a tight, light-resistant container at 20° - 25°C (68° - 77°F). This medication is distributed by GSMS, Incorporated in Camarillo, CA 93012 USA.*

Chemical Structure - dexlansoprazole 01

Chemical Structure - dexlansoprazole 01

Figure 1 - dexlansoprazole 02

Figure 1 - dexlansoprazole 02

This is a graph showing plasma concentration (in ng/mL) of Dexlansoprazole at 30mg and 60mg over time (in hours). The concentrations decrease over time for both doses.*

* 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.