No Foundation Foundation Fair
Product Images NDC 62742-4060

Product Visual Gallery

This gallery contains 2 technical images submitted to the FDA as part of the official labeling for No Foundation Foundation Fair (NDC 62742-4060). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.

As provided by Allure Labs, Inc, these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.

FDA Label Image

Image Of Product: Perricone Md No Foundation Foundation Fair 30ml (Imagenfff)

The Perricone MD No Foundation Foundation Fair is a patented and researched formula by a dermatologist, Nicholas Perricone. It is a multi-purpose product that provides natural translucent coverage and non-chemical SPF 30 broad-spectrum protection. The product helps correct skin undertones while boosting its moisture level throughout the day with high potency ingredients infused within. The formula is also designed to firm the skin's appearance, soften lines, wrinkles, and pores. It is not for children, and users are advised to reapply every two hours. The product is made in the USA and distributed by NV Perricone LLC, Meriden CT 06450.*

FDA Label Image

Image Of Ther Product: Perricone Md No Foundation Foundation Fair 59 mL (Imagenfff20)

Perricone MD No Foundation Foundation Fair is a multi-purpose formula that provides natural translucent coverage to the skin while protecting it with SPF 30. The product is unique because it is patented, researched, and formulated by Nicholas Perricone, M.D., a board-certified dermatologist and anti-aging expert. It delivers powerful results and boosts the skin's moisture level throughout the day. The product is formulated with specially treated pigments that soften the look of lines, wrinkles, and pores, making the skin look smooth and naturally radiant.*

* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.