Pregabalin Capsule
Product Images NDC 71610-765
View Photos of Packaging, Regulatory Labels, and Product Appearance
Product Visual Gallery
This gallery contains 15 technical images submitted to the FDA as part of the official labeling for Pregabalin (NDC 71610-765). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.
As provided by Aphena Pharma Solutions - Tennessee, Llc, these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.
Product Images & Figures Index
Aphena Pharma Solutions (TN)
Figure 1 (Pregabalincaps Fig01)
Figure 2 (Pregabalincaps Fig02)
Figure 3 (Pregabalincaps Fig03)
Figure 4 (Pregabalincaps Fig04)
Figure 5 (Pregabalincaps Fig05)
Figure 6 (Pregabalincaps Fig06)
Figure 7 (Pregabalincaps Fig07)
Figure 8 (Pregabalincaps Fig08)
Figure 9 (Pregabalincaps Fig09)
This text appears to be a table showing the estimated percentage of subjects without LTR (Long Term Relief) for a certain study. The table includes percentages ranging from 100% to 0%, spaced at intervals of 10%. The table also mentions two groups: "Progabain" and "Placebo". The numbers "20", "40", "80", and "120" are listed horizontally beneath the headings "Days". It is unclear what exactly these numbers signify without additional context.*
Figure 11 (Pregabalincaps Fig10)
Figure 12 (Pregabalincaps Fig11)
This text provides information on the percent of subjects improved over a period of time. The data shows a range of values from 100 to 280, with specific values at 210, 220, 230, 240, 250, 260, and 270. It also mentions the comparison between Pregabalin and Placebo. However, without further context or additional information, it is difficult to interpret the significance of these numbers.*
Cockcroft And Gault Equation (Pregabalincaps Formula)
Chemical Structure (Pregabalincaps Str)
* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.