Product Images Leflunomide

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Product Label Images

The following 8 images provide visual information about the product associated with Leflunomide NDC 50268-478 by Avpak, 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.

10 - 477 15 10mg

10 - 477 15 10mg

Leflunomide Tablets, USP is a prescription medicine that comes in a pack of 50 tablets (5 x 10) unit dose. Each tablet contains 10 mg of leflunomide. It is recommended to be stored at a temperature of 25°C (77°F) with excursions allowed from 15° to 30°C (59° to 86°F). It should be protected from light. The usual dosage is mentioned in the package insert. The medicine is manufactured for AvKARE, Pulaski, TN 38478.*

20 - 478 15 20mg

20 - 478 15 20mg

This is a description of Leflunomide tablets, a prescription medicine that contains 20mg of the active ingredient. The tablets are available in a package of 50 units, each containing 10 tablets. The tablets should be stored at a temperature range of 15° to 30°C and protected from light. The package insert should be consulted for dosage information. The tablets are manufactured for AVKARE, and the label includes a lot number and a manufacturing date.*

Figure1.jpg - Figure1

Figure1.jpg - Figure1

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Figure2.jpg - Figure2

The text describes the percentage of responders in trial 1 for ACR (American College of Rheumatology) over the course of 6 months. There is a chart displaying the percentage of responders over time. There are four treatment groups represented by the abbreviations "pL", "NTX", "4", and "LEF". It is unclear what these treatments refer to without additional context. The method of calculation is last observation carried forward.*

Figure3.jpg - Figure3

Figure3.jpg - Figure3

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Structure1.jpg - Structure1

Structure1.jpg - Structure1

Structure2.jpg - Structure2

Structure2.jpg - Structure2

* 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.