Product Images Rizatriptan Benzoate
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 5 images provide visual information about the product associated with Rizatriptan Benzoate NDC 71335-2979 by Bryant Ranch Prepack, 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 - lbl713352979
This text contains information about a medication called Rizatriptan Benzoate Tablets, USP. Each tablet contains 7.265 mg of Rizatriptan Benzoate, which is equivalent to 5 mg of Rizatriptan. It provides directions for usual adult dosage, storage conditions, and precautions such as keeping the medication out of the reach of children. The package insert QR code is mentioned for further details. The medication is to be dispensed in a tight, light-resistant container. It also provides the NDC (National Drug Code) number and the details of the manufacturer, Bryant Ranch Prepack, Inc., and Alkem Laboratories Ltd.*
rizatriptan-Fig-1 - rizatriptan Fig 1
This text provides a graphical representation of the probability of response to different dosages of Rizatriptan Benzoate compared to a placebo over a period of 10 hours post-dose. The percentages indicate the likelihood of response at different time points after taking either the placebo or varying doses of Rizatriptan Benzoate.*
rizatriptan-Fig-2 - rizatriptan Fig 2
This is information related to the estimated probability of needing additional medication or rescue intervention after taking either Rizatriptan Benzoate 5 mg or Rizatriptan Benzoate 10 mg at various hours post-dose, as compared to a placebo. The data indicates the percentage of users that may require remedication or rescue intervention within the provided time frame.*
rizatriptan-Fig-5 - rizatriptan Fig 5
rizatriptan-Structure - rizatriptan Structure
* 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.
