Product Images Fluphenazine Decanoate

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Product Label Images

The following 3 images provide visual information about the product associated with Fluphenazine Decanoate NDC 55150-267 by Eugia Us Llc, 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.

PACKAGE LABEL-PRINCIPAL DISPLAY PANEL - 125 mg per 5 mL (25 mg / mL) - Container Label - fluphenazine fig1

PACKAGE LABEL-PRINCIPAL DISPLAY PANEL - 125 mg per 5 mL (25 mg / mL) - Container Label - fluphenazine fig1

Fluphenazine Decanoate is an injection intended for intramuscular or subcutaneous use. Each 5mL vial contains 125 mg of fluphenazine decanoate USP, equivalent to 18.5 mg of fluphenazine, which is a drug commonly used to treat psychotic disorders. It also includes benzyl alcohol as a preservative and sesame oil. The recommended dose is indicated in the insert, and it should be stored at a temperature between 20-25°C (68-77°F) protected from light. The product is manufactured by Auromedics Pharma LLC and has the NDC 55150-267-05 code.*

PACKAGE LABEL-PRINCIPAL DISPLAY PANEL - 125 mg per 5 mL (25 mg / mL) - Container-Carton (1 Vial) - fluphenazine fig2

PACKAGE LABEL-PRINCIPAL DISPLAY PANEL - 125 mg per 5 mL (25 mg / mL) - Container-Carton (1 Vial) - fluphenazine fig2

This is a description of a medication called Fluphenazine Decanoate Injection, USP manufactured by AuroMesics Pharma. It comes in a 5mL multiple dose vial with a concentration of 125mg per 5 mL (25mg/mL). It is intended for intramuscular or subcutaneous use and must be stored at controlled room temperature between 20 and 25 degrees Celsius. The medication is used to treat psychotic disorders. The text also includes prescription and distribution information.*

Fluphenazine Decanoate Chemical Structure - fluphenazine str

Fluphenazine Decanoate Chemical Structure - fluphenazine str

* 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.