Structure (Pirfenidone 01)
Pirfenidone Capsule
Product Images NDC 0781-2158
View Photos of Packaging, Regulatory Labels, and Product Appearance
Product Visual Gallery
This gallery contains 6 technical images submitted to the FDA as part of the official labeling for Pirfenidone (NDC 0781-2158). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.
As provided by Sandoz Inc, these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.
Figure 1 (Pirfenidone 02)
This document appears to be displaying a chart that compares the effectiveness of Pirfenidone and Placebo in treating a medical condition related to pulmonary function. The chart measures the percentage of patients who experienced a decline or an increase in %FVC (Forced Vital Capacity) after a period of 52 weeks. The chart indicates that 25% of patients receiving Pirfenidone experienced a decrease in %FVC, while 20% experienced an increase. In contrast, among patients receiving Placebo, 45% experienced a decrease, while 0% experienced an increase. The bottom row of the chart shows the absolute change in %FVC from baseline to week 52 for both treatments.*
Figure 2 (Pirfenidone 03)
Figure 3 (Pirfenidone 04)
Table.jpg (Pirfenidone 06)
This is a dosing schedule for Pirfenidone Capsules 267mg. The table shows the recommended number of pills to take in the morning, afternoon, and evening during the first three weeks of treatment. During days 1-7, one pill should be taken during breakfast, lunch, and dinner for a total of three pills per day. During days 8-14, two pills should be taken during breakfast, lunch, and dinner for a total of six pills per day. From day 15 onwards, three pills should be taken during breakfast, lunch, and dinner for a total of nine pills per day.*
Label (Image 01)
* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.
