Figure 1 (Figure 1)
Progesterone Capsule
Product Images NDC 16714-157
View Photos of Packaging, Regulatory Labels, and Product Appearance
Product Visual Gallery
This gallery contains 4 technical images submitted to the FDA as part of the official labeling for Progesterone (NDC 16714-157). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.
As provided by Northstar Rx Llc, these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.
Principal Display Panel (100 mg Capsule Bottle Label)
Progesterone Capsules contain 100mg of micronized progesterone per capsule. The usual dosage is to be determined by the package insert. It is recommended to store the capsules at room temperature in a tight, light-resistant container and to protect from excessive moisture. These capsules are manufactured by Laboratorios Ledn Farma, S.A., in Spain and are distributed by Northstar Rx LLC. A patient leaflet with drug information is provided to every patient.*
Principal Display Panel (200 mg Capsule Bottle Label)
This is a description of Progesterone Capsules with a strength of 200mg manufactured by Laboratorios Ledn Farma, S.A. in Spain and distributed by Northstar Rx LLC in Memphis, TN. The medication comes in a container with 100 capsules each, and it should be stored at room temperature between 20°C to 25°C. The package insert contains information on the typical dosage. The medication is not to be used for individuals who are allergic to peanuts. The text specifies that the product must be dispensed in a tightly sealed, light-resistant container to safeguard from extreme moisture, and it warns to keep all drugs and this product, in particular, away from children. The text contains the National Drug Code for this medication, 16714-158-01.*
Chemical Structure (Prog Structure)
* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.
