Product Images Sumatriptan

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 4 images provide visual information about the product associated with Sumatriptan NDC 61919-300 by Direct Rx, 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.

image description - FIGURE01

image description - FIGURE01

This is a graph that shows the estimated probability of achieving initial headache response within 4 hours of treatment in pooled trials 1, 2, and 3. The X-axis represents time in minutes from initial dose, while the Y-axis represents the estimated probability of achieving response. The graph indicates that the probability of achieving initial headache response within 4 hours of treatment is 100% at the time of initial dose and decreases over time.*

image description - FIGURE02

image description - FIGURE02

This is a figure that shows the estimated probability of patients taking a second dose of Sumatriptan tablets or other medication to treat migraine over the 24 hours following the initial dose of study treatment in pooled trials 1, 2, and 3. The horizontal axis indicates the time in hours from the initial dose, and the vertical axis shows the probability of taking a second dose. There is a legend showing the percentage values for the probability of taking a second dose of medication.*

image description - MODULE1

image description - MODULE1

image description - label1

image description - label1

The text appears to be describing a medication named SUMATRIPTAN 100mg. It provides information about the NDC codes, lot expiration date, and the number of tablets in the package. It also mentions that each tablet contains sumatriptan succinate USP equivalent to 100mg of sumatriptan. The text includes a lot of obscure characters and symbols.*

* 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.