Product Images Nucynta

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Product Label Images

The following 4 images provide visual information about the product associated with Nucynta NDC 55700-792 by Quality Care Products, Llc, 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.

image description - New Doc 2019 09 18 12.45.13 1

image description - New Doc 2019 09 18 12.45.13 1

This is a warning label for a medication called Tapentadol. It is packaged and distributed by MZ&/ @afle p’&dm. The medication comes in the form of yellow, round tablets with the imprint O;M;50. The GTIN number is 00355700792305 and the NDC number is 55700-0792-30, which corresponds to a bottle of 30 tablets. The label warns that the medication may be habit-forming and advises to keep it out of children's reach. The medication should be stored at a temperature between 68 and 77 degrees F. The tablets contain Tapentadol and should only be taken under the guidance of a physician, as described in the manufacturer's insert. There is also an expiration date and a lot number mentioned.*

Chemical Structure - nucynta 01

Chemical Structure - nucynta 01

Figure 1 - nucynta 02

Figure 1 - nucynta 02

This seems to be a medical document that displays the effectiveness of NUCYNTA® (50mg, 75mg, and 100mg) in pain management, compared to a placebo. It includes percentages of patients who improved and percent improvement in pain from baseline at hour 45. Not available.*

Figure 2 - nucynta 03

Figure 2 - nucynta 03

The text appears to be a graph showing the percentage of patients who had improvement in pain after taking Nucynta in 50mg and 75mg doses versus a placebo. The x-axis shows the percent improvement in pain from baseline on day 5, and the y-axis shows the percentage of patients improved. However, some symbols are missing, making the data hard to interpret accurately.*

* 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.