Product Images Frovatriptan
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 7 images provide visual information about the product associated with Frovatriptan NDC 50742-299 by Ingenus Pharmaceuticals, Llc, 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 appears to be a table showing the estimated probability of response of Frovatriptan Succinate Tablets in comparison to a placebo over a period of time from the initial dose. The table shows the probability of response starting from 100% and decreasing in 10% increments down to 0%. Time from the initial dose is shown as the only column next to the probability percentages. The dosage of Frovatriptan Succinate Tablets is mentioned to be 2.5 mg.*
This is a chart displaying the estimated probability of remedication or rescue for placebo and Frovatriptan Succinate Tablets 2.5 mg over a period of 24 hours, with time intervals of 4 hours. The probability starts at 100% and gradually decreases every 10% until it reaches 0%.*
This is a product label for Frovatriptan Succinate, a tablet medication used to treat migraines. The tablets are available in 2.5 mg dosage strength and are manufactured by Ingenus. The lot number and expiration date are listed on the label. There is also a mention of a higher strength tablet at 25 mg dosage.*
Bugz is a medication in tablet form that contains 3.91 g of frovatriptan succinate, equal to 2.5 mg of frovatriptan, designed to relieve migraines. It is important to keep this medicine out of reach of children and store it at 25°C, excursions permitted to 15°-30°C. The medication is produced by Ingenus Pharmaceuticals, LLC, in India and is packaged in a blister card containing 9 tablets. The neutral code is DRUGS/AP/01/2006, and there is additional miscellany, but the output is unreadable.*
* 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.