Product Images Duloxetine Hydrochloride

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 14 images provide visual information about the product associated with Duloxetine Hydrochloride NDC 50771-203 by Yaopharma Co., Ltd., 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.

structural formula - 1566564938743

structural formula - 1566564938743

20mg - 20mg60

20mg - 20mg60

30mg - 30mg90

30mg - 30mg90

60mg - 60mg30

60mg - 60mg30

90beaf4a 3b90 2d90 e053 2995a90a335e

90beaf4a 3b90 2d90 e053 2995a90a335e

Not available.*

90beaf4a 3b91 2d90 e053 2995a90a335e

90beaf4a 3b91 2d90 e053 2995a90a335e

90bf2493 e18e 655e e053 2995a90ac94e

90bf2493 e18e 655e e053 2995a90ac94e

F1 - F1

F1 - F1

The text provides information about the proportion of patients with relapse for two different treatments: placebo and Duloxetine delayed-release capsules. The data is presented in a graph, showing the time from randomization to relapse in days. Unfortunately, specific values or percentages are not readable from the text.*

F2 - F2

F2 - F2

The text appears to be a graph showing the proportion of patients with relapse over time for two treatments: placebo and duloxetine delayed-release capsules. The graph displays the time from randomization to relapse in days on the x-axis and the proportion of patients on the y-axis. The specific data points on the graph are not legible.*

F3 - F3

F3 - F3

F4 - F4

F4 - F4

F7 - F7

F7 - F7

F8 - F8

F8 - F8

F9 - F9

F9 - F9

This text appears to be showing the percentage of patients who have improved, along with some data points related to pain improvement. The data includes percentages of improvement and specific numbers for pain improvement from baseline. However, without more context or legible text, it is difficult to provide a more detailed description.*

* 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.