Product Images Divalproex Sodium

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 5 images provide visual information about the product associated with Divalproex Sodium NDC 55154-2345 by Cardinal Health 107, 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.

Bag label - 283AF6D2 8EA2 4225 B2E7 A2057DBDB793 00

Bag label - 283AF6D2 8EA2 4225 B2E7 A2057DBDB793 00

Divalproex Sodium Extended-Release Tablets are available in a package of 10 tablets. Each tablet has a valproic acid activity of 500mg and is coated with a film. The package insert includes prescribing information, precautions, and warnings. The medication should be stored at a temperature of between 20-25°C. This package is not suitable for child-resistant storage and is exclusively intended for institutional use. There are multiple companies involved in the production and distribution of this medication.*

10 - divalproex sodium extended release tablets usp 1

10 - divalproex sodium extended release tablets usp 1

Figure 1 - divalproex sodium extended release tablets usp 2

Figure 1 - divalproex sodium extended release tablets usp 2

Figure 2 - divalproex sodium extended release tablets usp 3

Figure 2 - divalproex sodium extended release tablets usp 3

This appears to be a graph showing the % Reduction in CPS (Chronic Pelvic Syndrome) Rate for patients who were administered High Dose and Low Dose Divalproex Sodium. The graph indicates that the High Dose had a higher percentage (around 100%) of patient improvement in CPS rate in comparison to the Low Dose (around 50%). The graph also shows the percentage of patients who experienced No Change and Worsening in their CPS rate.*

Figure 3 - divalproex sodium extended release tablets usp 4

Figure 3 - divalproex sodium extended release tablets usp 4

* 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.