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 68788-7848 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 300mg (CIV)

Gabapentin Capsules 300mg (CIV)

Product description: Gabapentin Capsules 300mg, a generic drug for Neurontin produced by ScieGen Pharmaceuticals, Inc. The capsules are available in a package of unspecified size and lot number, and it is cautioned that the transfer of the product is prohibited by federal law. The label includes information on warnings, insurance, and a National Drug Code (NDC).*

Figure 1 - image 01

Figure 1 - image 01

This appears to be a table or graph showing mean pain scores for a test group. The table includes different doses of a medication called "Parkod" (with both fixed and titrated doses) as well as a placebo and gabapentin at 3600 mg/day. The mean pain score is listed as 0 at baseline with weeks indicated, but without further context, the purpose or results of the test cannot be determined.*

Figure 2 - image 02

Figure 2 - image 02

Figure 3 - image 03

Figure 3 - image 03

Cockcroft and Gault Equation - image 04

Cockcroft and Gault Equation - image 04

Gabapentin Structural Formula - image 05

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

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.