Atovaquone Suspension
Product Images NDC 51407-642

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Product Visual Gallery

This gallery contains 3 technical images submitted to the FDA as part of the official labeling for Atovaquone (NDC 51407-642). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.

As provided by Golden State Medical Supply, Inc., these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.

Product Images & Figures Index

FDA Label Image

51407-642-87cb.jpg (51407 642 87cb)

51407-642-87cb.jpg (51407 642 87cb)
This is a description of a medication named Atovaquone Oral Suspension, USP. It contains 750 mg of Atovaquone, which is used for treatment purposes. Dosage recommendations and storage instructions are given. The manufacturer of the medication is CoreRx, Inc. and it is marketed by GSMS, Incorporated. The bottle should not be used if the tamper-evident seal is broken or missing. The text also includes some unclear or unreadable characters.*
FDA Label Image

51407-642-87ol.jpg (51407 642 87ol)

51407-642-87ol.jpg (51407 642 87ol)
This is a description of a medication called atovaquone oral suspension, USP. Each 5 mL (1 teaspoonful) of the medication contains 750 mg of atovaquone, USP. The dosage information is mentioned in the accompanying prescribing information. This medication should not be frozen and should be dispensed in a tight container as defined in USP. The bottle should be shaken gently before using. This medication should be kept away from children. The tamper-evident seal on the bottle should not be broken or missing. This medication should be stored at a temperature between 20° - 25°C (68° - 77°F). The company that manufactures this medication is CoreRx, Inc. and it is marketed by GSMS, Incorporated.*
FDA Label Image

Structure (Structure)

Structure (Structure)

* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.