Product Images Nucynta ER
View Photos of Packaging, Labels & Appearance
- Chemical Structure - nucynta 01
- Figure 1 - nucynta 02
- Figure 2 - nucynta 03
- Figure 3 - nucynta 04
- PRINCIPAL DISPLAY PANEL - 50 mg Tablet Bottle Label - nucynta 05
- PRINCIPAL DISPLAY PANEL - 100 mg Tablet Bottle Label - nucynta 06
- PRINCIPAL DISPLAY PANEL - 150 mg Tablet Bottle Label - nucynta 07
- PRINCIPAL DISPLAY PANEL - 200 mg Tablet Bottle Label - nucynta 08
- PRINCIPAL DISPLAY PANEL - 250 mg Tablet Bottle Label - nucynta 09
Product Label Images
The following 9 images provide visual information about the product associated with Nucynta ER NDC 24510-116 by Collegium Pharmaceutical, 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.
Figure 1 - nucynta 02

This is a graph depicting the percent improvement of pain from baseline at week 15 of the treatment period for patients using either a placebo or the medication Nucynta ER. The x-axis shows percentage increments from 0 to 100, and the y-axis shows the number of patients with different degrees of pain improvement. The data labels indicate improvement percentages of 10, 20, 30, 40, 50, 60, 70, 80, 90, and 100.*
Figure 2 - nucynta 03

This is a chart that shows the percentage of patients who reported improvement in pain after taking either a placebo or Nucynta ER medication for 12 weeks. The chart provides data points at intervals of 10, ranging from 0 to 100. The numbers range from 20 to 100% improvement.*
Figure 3 - nucynta 04

This is a chart showing the percent of patients who improved their pain from baseline after taking either placebo or NUCYNTA® ER. The chart shows different percentage ranges and the number of patients who fell within each range after 12 weeks. The chart suggests that NUCYNTA® ER was more effective than placebo in improving pain.*
* 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.