Product Images Duloxetine
View Photos of Packaging, Labels & Appearance
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- Label Image - lbl713351672
Product Label Images
The following 10 images provide visual information about the product associated with Duloxetine NDC 71335-1672 by Bryant Ranch Prepack, 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.
duloxetine-fig7 - duloxetine fig7

This appears to be a chart displaying the percentage of patients who have improved in terms of pain relief after taking either a placebo or a medication called Didoreine. The X-axis shows different time points during the study, and the Y-axis measures the percentage of patients who have experienced pain relief. The exact nature of the study and the conditions being treated are not indicated in the available text.*
duloxetine-fig8 - duloxetine fig8

The text states the percentage of patients improved with pain relief. The data is presented in a table with different values. The percentage of improvement ranges from 0 to 100. The source of the data is not mentioned.*
duloxetine-figure2 - duloxetine figure2

This appears to be a graph showing the proportion of patients with relapse over time from randomization in a clinical study. It shows the proportion of patients with relapse at different time points marked in days on the x-axis and the proportion on the y-axis. However, without more information about the study or the specific context, it's unclear what the relapse refers to or what the significance of the data is.*
Label Image - lbl713351672

This appears to be the label information for a medication called "Cymbalta 30mg Capsule" produced by Alkem Laboratories Ltd. The label provides information on dosage, storage, and potential side effects, as well as an expiration date and a National Drug Code (NDC) number. The package was prepackaged by Bryant Ranck.*
* 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.