Product Images Perphenazine

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Product Label Images

The following 4 images provide visual information about the product associated with Perphenazine NDC 53808-0938 by State Of Florida Doh Central Pharmacy, 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.

Label Image for 16mg - 16mg qualitest

Label Image for 16mg - 16mg qualitest

This is a prescription-only medication called Perphenazine, in the form of a tablet with a strength of 16mg. The medication is manufactured by Qualtest and the lot number is C0430912A. The lot number of the packaging is 0200201348 and the expiration date is 08312013. The package was distributed by DOH.S Control Pharmacy and the universal product code is 3060350632.*

Label Image for 4mg - 4mg qualitest

Label Image for 4mg - 4mg qualitest

Perphenazine is a medication available in the format of 4mg tablets. The package contains 30 pills, and it was manufactured by Qualitest with the batch number C22008134. The drug was packaged at Dok Central Pharmacy and will expire on March 7th, 2014, as per the label. Unfortunately, the meaning behind "UPGH 306035061215" could not be determined.*

Label Image for 2mg - Perphenazine 2mg

Label Image for 2mg - Perphenazine 2mg

Perphenazine is a medication available in tablet form with a strength of 2mg. This medication is available on prescription only, and one pack contains 30 tablets. The manufacturer of the medication is Qualitest, and the lot number of this particular pack is C05001134. The pack was produced on January 8th, 2014, and has an expiration date of August 7th, 2014. The package was packed by DO Central Pharmacy located in Tallahassee, FL and can be identified with the UPC code: 306035080287.*

This is the structual formula for Perphenazine. - perphenazine 1

This is the structual formula for Perphenazine. - perphenazine 1

* 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.