Product Images Gabapentin
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 7 images provide visual information about the product associated with Gabapentin NDC 68071-2366 by Nucare Pharmaceuticals,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.
PDP - 68071 2366 1
A medication called Gabapentin 300mg is being described with its lot number, NDC number, manufacturer NDC number, serial number, GTIN and an expiration date. The packaging warns to keep out of reach of children and lists the FDA number to report any side effects. Store at temperature controlled between 59-86°F.*
Figure 1 - image 01
The text is describing a graph/chart displaying the mean pain score for two different treatments over a course of weeks. One treatment involves titration (dose adjustment) of a medication called "Parkod" and the other involves a fixed dose. There is also a placebo group and a group taking a medication called "Gabapentin" at a dosage of 3600 mg/day. The graph/chart shows a baseline measurement and pain scores for each treatment group over the course of several weeks.*
Figure 2 - image 02
The text describes a graph showing the mean pain score of a study group over a 4-week period. The study involved testing the effectiveness of a placebo and two different doses of Gabapentin (1800 mg/day and 2400 mg/day) on pain reduction. The X-axis represents the weeks of the study, and the Y-axis represents the mean pain score. The baseline pain score was taken before the study began. The graph shows a decrease in mean pain scores for all three groups, with the group taking Gabapentin at 2400 mg/day showing the most significant reduction in pain.*
Figure 3 - image 03
Cockcroft and Gault Equation - image 04
Gabapentin Structural Formula - image 05
image-09 - image 09
* 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.
