Galantamine Tablet, Film Coated
Product Images NDC 68084-729
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 Galantamine (NDC 68084-729). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.
As provided by American Health Packaging, 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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The text appears to be a chart showing the cumulative percentage of patients based on changes in score points, as well as the change in ADAS-cog from baseline, for a placebo group and two different dosages (24mg/day and 32mg/day) of an unknown medication. Therefore, the context of the chart is not clear, but it may be related to the efficacy or effectiveness of the medication.*
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This appears to be a table or chart showing the percentage of patients who experienced certain levels of improvement or decline while taking a placebo or a medication at varying doses (presumably for a medical condition). The medication is not specified, and the table does not contain any other meaningful information.*
Structure
Galantamine Hydrobromide Structural Formula (Image 01)
This is a medication with the NDC code 68084-729-21 called Galantamine Tablets, USP that comes in a package containing 30 tablets. Each tablet contains Galantamine hycrobromics USP equivalent to 4 mg of galantamine base. The recommended dosage can be found in the prescription information. It should be stored between 15-80°C and kept out of the reach of children. The packaging has been distributed by the American Health Packaging company.*
Figure 1: Time-course Of The Change From Baseline In Adas-cog Score For Patients Completing 21 Weeks (5 Months) Of Treatment (Image 02)
* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.