Product Images Propoxyphene And Acetaminophen

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Product Label Images

The following 3 images provide visual information about the product associated with Propoxyphene And Acetaminophen NDC 68387-100 by Keltman Pharmaceuticals Inc., 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.

This is an image of the label for Pink Propoxyphene Napsylate and Acetaminophen Tablets 100 mg/650 mg. - Darvocet N 100

This is an image of the label for Pink Propoxyphene Napsylate and Acetaminophen Tablets 100 mg/650 mg. - Darvocet N 100

The text describes a medication called Generic Darvocet-N 100 containing Propoxyphene Napsylate and Acetaminophen 100mg/650mg. It comes in the form of tablets, and each tablet contains 100mg Propoxyphene Napsylate and 650mg Acetaminophen. The medication is available in bottles of 60 tablets and requires a prescription. The lot number for the medication is 65L0BA 2, and the expiry date is 12/2010. The medication is manufactured for Qualtest Pharmaceuticals and distributed by Ketman Pharmaceuticals. The dosage and packaging inserts should be followed. The medication should be kept out of reach of children and stored at controlled room temperature. The text also gives caution regarding the transfer of the drug and advises seeking medical advice if side effects occur or if symptoms persist.*

This is an image of the structural formula for Propoxyphene Napsylate. - propoxy 1

This is an image of the structural formula for Propoxyphene Napsylate. - propoxy 1

This is an image of the structural formula of Acetaminophen. - propoxy 2

This is an image of the structural formula of Acetaminophen. - propoxy 2

CsHoNO is a chemical compound with a molecular weight of 151.16. It is not possible to provide further information as the text refers only to the compound's chemical formula and molecular weight.*

* 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.