Figure1 (Figure1)
Gabapentin
Product Images NDC 50090-2794
View Photos of Packaging, Regulatory Labels, and Product Appearance
Product Visual Gallery
This gallery contains 7 technical images submitted to the FDA as part of the official labeling for Gabapentin (NDC 50090-2794). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.
As provided by A-s Medication Solutions, these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.
Figure2 (Figure2)
This text appears to be a table showing a medication study with two different periods: a 3-week dose titration period and a 4-week fixed dose period. The table includes information about the placebo group and a group that received Gabapentin in doses of either 1800 mg/day or 2400 mg/day. There are also mean pain scores for each group at various weeks.*
Figure3 (Figure3)
The given text displays a chart with different percentages listed on the Y-axis and a list of studies on the X-axis. The chart represents the proportion of responders with more than 50% reduction in pain score in controlled PHN Studies. The chart shows Study 1 and Study 2, with different percentages for each category listed under the studies. The chart has a note on the top stating "#p<001 and O b<0,001".*
Figure4 (Figure4)
Label Image (Lbl500902794)
Scale (Scale)
This text likely represents medical data, specifically information related to calculating the estimated creatinine clearance (CLCr) for a patient. The age and serum creatinine level are key factors in this calculation, although there seems to be some missing or unclear information. A correction factor of 0.85 appears to be relevant for female patients, but the exact value of CLCr cannot be determined without additional information.*
Structuralformula (Structuralformula)
* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.
