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 68788-7774 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 800mg 500tab

gabapentin 800mg 500tab

This is a description of Gabapentin tablets 800mg manufactured by ScieGen Pharmaceuticals, Inc. It is a generic version of Neurontin. Each tablet contains 800mg of gabapentin. The tablets are shipped in a package with expiry dates and lot numbers. The tablets should be stored at room temperature and kept out of reach of children. The tablets are white, scored, and imprinted with 178 /S G. It is a controlled substance and can only be taken by the patient it is prescribed for. The rest of the text is not available.*

Figure 1 - image 01

Figure 1 - image 01

This appears to be a chart or table with headings "Mean Pain Score", "0", "4", "Work Dose Tiration", "Parkod", "Week Fixed Dose Period", "O-Placebo", "# Gabapentin, 3600 mg/day", "Baseline", and "Weeks". It is not clear what the context or purpose of the chart is.*

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.