Product Images Xerava

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 3 images provide visual information about the product associated with Xerava NDC 71773-050 by Tetraphase 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.

100 mg vial

100 mg vial

XERAVA (eravacycline) is a sterile powder that must be reconstituted and diluted for intravenous infusion only. It is supplied in 100mg vials and each vial is not labeled for individual sale. Before reconstitution, XERAVA should be refrigerated, protected from light, and kept in the carton. It should be used within 1 hour of reconstitution and within 24 hours of dilution, or within 10 days when refrigerated. Any unused product should be discarded. Parenteral drug products should be visually inspected for particulate matter after reconstitution. XERAVA is distributed by Tetraphase Pharmaceuticals, Inc. in Waltham, MA. Please see the prescribing information for full directions for use.*

50 mg carton

50 mg carton

This is a pharmaceutical product called "eravacycline" that comes in a single-dose vial which contains 50 mg per vial. It is a sterile powder that must be reconstituted and diluted before intravenous infusion. The product includes inactive ingredients such as mannitol, sodium hydroxide, and hydrochloric acid. The prescribing information should be consulted for proper use, and the vial should be kept refrigerated between 2°C to 8°C (36°F-46°F) to avoid light exposure. The reconstituted solution from the vial should be transferred to an IV bag within 1 hour and used within 24 hours when stored at room temperature or within 10 days when stored refrigerated. The product should be visually inspected for particulate matter before use.*

Chemical Structure - image 01

Chemical Structure - image 01

* 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.