Product Images Flucelvax
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 4 images provide visual information about the product associated with Flucelvax NDC 70461-554 by Seqirus 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.
Principal Display Panel – 0.5 mL Carton Label - flu2t 0004 01
This is a description of an influenza vaccine called FLUCELVAX. The vaccine is recommended for individuals 6 months of age and older and is administered intramuscularly. It contains specific strains of the influenza virus and is prepared from virus propagated in Madin Darby Canine Kidney (MDCK) cells. The manufacturing process involves inactivation with beta-propiolactone (BPL) and the use of materials such as polysorbate 80, cetyltrimethylammonium bromide (CTAB), and beta-propiolactone. The vaccine does not contain preservatives and should be stored between 2-8°C. The product is manufactured by Seqirus Inc. in Holly Springs, NC, and distributed by Seqirus USA Inc. in Summit, NJ, USA.*
Principal Display Panel – 0.5 mL Syringe Label - flu2t 0004 02
This is a description of an influenza vaccine called FLUCELVAX® with the 2024-2025 formula. It is in a 0.5 mL dose for use in individuals aged 6 months and older. Manufactured by Seqirus Inc. with US License No. 2049, the product has the NDC code 70461-654-04.*
Principal Display Panel – 5 mL Carton Label - flu2t 0004 03
Principal Display Panel – 0.5 mL Vial Label - flu2t 0004 04
This is a description of an Influenza Vaccine in a multi-dose vial for use in persons 6 months of age and older. The vaccine should be stored between 2 — 8°C (36 — 46°F) and should not be frozen. It has a dose of 0.5 mL and the 2024 - 2025 formula. The vaccine is manufactured by Segirus Inc. in Holly Springs, NC and distributed by Seqirus USA Inc. in Summit, NJ.*
* 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.
