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 70934-950 by Denton Pharma, Inc. Dba Northwind Pharmaceuticals, 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.
This is a description of Gabapentin tablets with NDC code 70934-950-30. The remaining text is not readable and cannot provide any useful information.*
This appears to be a medical formula for calculating the Creatinine Clearance (CLCr) of a female patient using their serum creatinine levels (mg/dL). However, without more context, it is difficult to provide a more specific description or interpretation.*
The text contains information about a clinical trial with a 4-week dose titration period and a 4-week fixed dose period. There are two treatment groups: placebo and gabapentin at a dose of 3600 mg/day. The text also displays a mean pain score of 10, but no context is provided for this score. There is some unreadable text in the form of symbols and characters.*
The text provides a table with four columns showing the mean pain score for participants during a four-week fixed dose period using different treatments. The treatments include a placebo and two doses of Gabapentin (1800mg/day and 2400mg/day). The table also includes a baseline column and data measured at week 1. No further information is available.*
This is a chart showing the proportion of responders in controlled PHN studies. It includes percentages ranging from 0% to 100%, with specific percentages shown for different treatments such as GBP 3600 and PBO, as well as different study groups. The figure also includes a note indicating that a p-value of less than 0.001 was observed in one or more of the studies.*
* 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.