Fibryga Kit
Product Images NDC 68982-347

View Photos of Packaging, Regulatory Labels, and Product Appearance

Product Visual Gallery

This gallery contains 16 technical images submitted to the FDA as part of the official labeling for Fibryga (NDC 68982-347). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.

As provided by Octapharma Usa 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.

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This text is a formula for calculating the dose of a medication based on the measured and target fibrinogen levels. The formula includes a conversion factor of 18 mg/dL per mg/kg body weight.*
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This text provides a formula to calculate dose in milligrams per kilogram of body weight using the difference between the target fibrinogen level and the measured fibrinogen level. The formula provides a conversion factor of 1.4 milligrams per deciliter per milligram per kilogram of body weight.*
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This is a table showing Virus Reduction Factor for enveloped and non-enveloped viruses in different production steps. The table lists some viruses such as HIVI, PRV, BVDV, HAV, and PPV. The methods for virus reduction are S/D treatment and Nanofiltration, and the reduction factor is measured in Log10. There is also a column for Cumulative Virus Reduction Factor (Log10).*
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This is a table of pharmacokinetic parameters of a drug in different age groups. The drug's half-life, maximum concentration in blood (Cmax), area under the curve (AUC), clearance rate, mean residence time, and volume of distribution at steady-state are all given in different units across three age groups: adults and adolescents (aged 21 and above), pediatric subjects aged 6 to <12 years, and pediatric subjects aged <6 years. The ranges and mean values of each parameter are also provided.*
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* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.