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 68788-7838 by Preferred 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.
Gabapentin Capsules, USP 400mg
This is a description of Gabapentin capsules, USP 400mg. The capsules are generic for Neurontin. Each capsule contains 400mg of Gabapentin. The product is manufactured by ScieGen Pharmaceuticals, Inc, and the product code is ENeo. The description includes batch and lot numbers but does not include instructions for use. Caution is stated regarding federally-prohibited transfer of the capsules.*
Figure 1 - image 01
This appears to be a table with columns representing different treatment options for pain management, including a fixed dose and a dose that is titrated (adjusted over time). The different treatment options may include a placebo or gabapentin at 3600 mg/day. The table also includes a baseline measurement and pain scores measured at different time points (weeks).*
Figure 2 - image 02
This appears to be a chart showing the results of a study evaluating the use of Gabapentin (at varying dosages) versus a placebo for pain management over a four-week period. The X-axis represents the weeks of the study and the Y-axis represents the mean pain score reported by participants. However, without further context or information, it is difficult to provide a more specific description or interpretation.*
Figure 3 - image 03
Cockcroft and Gault Equation - image 04
Gabapentin Structural Formula - image 05
Figure 4. Responder Rate in Patients Receiving gabapentin Expressed as a Difference from Placebo by Dose and Study: Adjunctive Therapy Studies in Patients ≥12 Years of Age with Partial Seizures - 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.