Product Images Mycophenolic Acid

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Product Label Images

The following 3 images provide visual information about the product associated with Mycophenolic Acid NDC 60429-016 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.

60429 016 12

60429 016 12

This text is about a medication called Mycophenolic Acid in Delayed-release Tablet form, with each tablet containing 180mg of mycophenolic acid, produced by GSMS Incorporated with dosage information included in the package insert. The medication should be dispensed in a tight, light-resistant container, and kept away from moisture. The recommended usage instructions are to not crush, chew, or cut the tablet, to take it on an empty stomach, 1 hour before or 2 hours after a meal. The medication should be kept at temperatures of 15-30°C (59-86°F) and stored between 20-25°C (68-77°F). GSMS Incorporated manufactured the medication in conjunction with Apotex Inc. A medication guide is provided separately for each patient, and the medication should be kept out of the reach of children.*

60429 017 12

60429 017 12

GSMS Incorporatea's Mycophenolic Acid Delayed-Release Tablets USP of 360mg are available in a bottle of 120 tablets. The medication guide should be provided to each patient by the pharmacist. The tablets should be stored at a temperature between 20-25°C (68°-77°F) with permitted excursions from 15°-30°C (59°-86°F). It should be dispensed in a light-resistant container and protected from moisture. The tablets should not be crushed, chewed, or cut, and should be taken on an empty stomach either 1 hour before or 2 hours after a meal. The tablets are manufactured by Apotex Inc. and packaged by GSMS, Incorporated in Camarillo, CA, 93012 USA.*

mycophenolic-structure - mycophenolicfigure

mycophenolic-structure - mycophenolicfigure

* 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.