Product Images Gabapentin
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 6 images provide visual information about the product associated with Gabapentin NDC 71335-1197 by Bryant Ranch Prepack, 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.
gabapentin fig1
This is a clinical trial report showing the mean pain score with a 4-week dose titration period followed by a 4-week fixed dose period with placebo and Gabapentin, 3600 mg/day. The baseline information is also included in the report.*
gabapentin fig2
The text provides a table with four different treatments (placebo, Gabapentin 1800 mg/day, Gabapentin 2400 mg/day, and a fixed dose period) for pain management. The table shows data for mean pain scores at baseline and during the treatment period. There is not enough information to determine the condition being treated or the efficacy of the treatments.*
gabapentin fig3
The text contains statistical data related to the proportion of patients in controlled PHN studies, specifically the percentage of responders (patients with a 50% reduction in pain score) at endpoint, for different treatments such as GBP 3600, PBO, GEBP 1800, GBP 2400. The figure shows different percentages ranging from 100% to 10%. Therefore, this text provides an overview of statistical data obtained in controlled PHN studies for different treatments.*
lbl7133511972
This text appears to be a label for a medication called "Neurontin 300mg". It comes in capsule form, is packaged by Bryant Ranck Prepack, and has an expiration date of MM/YY. The drug is produced by Alkem Laboratories Limited and has an NDC number. The label includes storage instructions to keep the drug at room temperature and a warning to keep it out of reach of children. The last line may be a UPC or barcode number.*
* 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.