Product Images Oxycodone And Acetaminophen

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 2 images provide visual information about the product associated with Oxycodone And Acetaminophen NDC 67296-0355 by Redpharm Drug, 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.

67296-0355 - doc20161118134338 001

67296-0355 - doc20161118134338 001

This is a description of a prescription drug containing a combination of Oxycodone and Acetaminophen, presented in tablet form. It comes in five different packages of 10, 15, 20, 30, and 50 tablets, each with a tight and child-resistant container and moisture protection. It should be stored in controlled room temperature and kept out of the reach of children. Federal law prohibits the transfer or sharing of this medication to other people than the patient for whom it was prescribed. The drug was made and distributed by Mallinckrodt Inc., and RedPharm Drug respectively and repackaged by Blenhesm Phasmacal, Inc. The lot number for the 5mg/325mg variant tablet is RADBAAXK. Furthermore, the packaging doesn't contain any dosage information.*

#60 - doc20170420102154 001

#60 - doc20170420102154 001

This is a description of a medication with the National Drug Code (NDC) number 67296-0355-7. The medication contains a combination of Oxycodone HCL and Acetaminophen with a strength of 5/325 mg. The package contains 60 tablets and the lot number is Z967601 with an expiration date of 06/21. The medication is only available with a prescription. The usual adult dosage information can be found on the package insert. The medication should be stored in a controlled room temperature between 20-25°C (68-77°F). The medication is manufactured by Mallinckrodt Inc. in Hazelwood, MO 63042 and distributed by Redpharm Drug in Eden Prairie, MN 55344.*

* 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.