Product Images Dronabinol

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 4 images provide visual information about the product associated with Dronabinol NDC 0904-7144 by Major Pharmaceuticals, 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.

carton label - FD8C5D57 0173 4F62 8FF0 D8147986A976 00

carton label - FD8C5D57 0173 4F62 8FF0 D8147986A976 00

This is a description for a medication called DRONABINOL in capsule form. The package comes with 30 capsules, each containing 8mg of Oronabinel. The medication is meant for prescription use only and comes with patient information to be dispensed by a pharmacist. The package is a Unit Dose package with NDC codes for easy identification. The product is made by MAJOR and precautions and warnings need to be followed. The text also includes a warning to keep the medication out of reach of children.*

carton label - FD8C5D57 0173 4F62 8FF0 D8147986A976 01

carton label - FD8C5D57 0173 4F62 8FF0 D8147986A976 01

This is a unit dose package of Dronabinol capsules, USP, which is a prescription medication containing 2.5 mg of Dronabinol per capsule. The product should be stored in a cool environment between 8 and 15 degrees Celsius and protected from freezing. The package is not child-resistant and is intended for institutional use only. Information on the medication can be found in the product insert or at the manufacturer's website.*

dronabinol-fig.jpg - dronabinol fig

dronabinol-fig.jpg - dronabinol fig

This text is a statistical report of the mean appetite change from baseline after taking Dronabinol, 2.5 mg BID versus a Placebo. The graph shows the comparison over a certain number of weeks. The "*p-value <0.05" indicates a significant difference between the two groups.*

dronabinol-str.jpg - dronabinol str

dronabinol-str.jpg - dronabinol str

* 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.