Product Images Divalproex Sodium
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Product Label Images
The following 7 images provide visual information about the product associated with Divalproex Sodium NDC 43353-547 by Aphena Pharma Solutions - Tennessee, 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.
Bottle Label 500mg - 43353 547
This is a medication called Divalproex NA ER which comes in a bottle of 60 tablets, each containing 500mg of the active ingredient. The NDC number for this medication is 43353-0547-53. The medication is manufactured by Mylan Pharmaceuticals Inc. The package was repackaged by Aphena Pharma BI85. The medication is used for treating seizures, bipolar disorder, and preventing migraines.*
Aphena Pharma Solutions - TN - Aphena
Divalproex Structural Formula - b1b571ea 8447 4fc1 8dd1 16ae8211dbe1 01
proportion of patients achieving any particular level of improvement was consistently higher for valproate than for placebo - b1b571ea 8447 4fc1 8dd1 16ae8211dbe1 02
The text describes a chart or graph showing the percentage reduction in CPS rate of patients taking Divalproex Sodium Delayed-Release compared to placebo. It indicates that 50% of patients experienced improvement while the rest experienced either no change or worsening.*
proportion of patients achieving any particular level of reduction was consistently higher for high dose valproate than for low dose valproate - b1b571ea 8447 4fc1 8dd1 16ae8211dbe1 03
This appears to be a chart showing the reduction in CPS rate for patients taking either high or low dose delayed-release divalproex sodium or divalproex sodium. The chart also shows the percentage of patients who experienced improvement, no change, or worsening.*
Figure 3 Mean Reduction in 4-Week Migraine Headache Rates - b1b571ea 8447 4fc1 8dd1 16ae8211dbe1 04
Mylan logo - b1b571ea 8447 4fc1 8dd1 16ae8211dbe1 05
* 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.