Inner Label2 (Inner Label2)
Live Tinted Hueguard 3-in-1 Mineral Sunscreen Moisturizer Primer Broad Spectrum Spf 30 Cream
Product Images NDC 82153-271
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Product Visual Gallery
This gallery contains 4 technical images submitted to the FDA as part of the official labeling for Live Tinted Hueguard 3-in-1 Mineral Sunscreen Moisturizer Primer Broad Spectrum Spf 30 (NDC 82153-271). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.
As provided by Live Tinted, 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.
Product Images & Figures Index
Inner Package (Inner Package)
Outer Package (Outer Package)
HUEGUARD is a sunscreen product that helps prevent sunburn and decreases the risk of skin cancer and early skin aging caused by the sun. It protects the skin from harmful UV rays, Capric Triglyceride, and blue light. The product is easy to apply and does not leave a white cast. The user needs to reapply it every two hours and pair it with a water-resistant SPF when swimming or sweating. The sunscreen is not intended to be used on damaged or broken skin and must be kept out of the eyes. If swallowed, medical attention is immediately necessary. The product is distributed by LIVETINTED® from Los Angeles, California, and is made in the USA.*
Outer Package2 (Outer Package2)
HUEGUARD is an all-in-one daily non-nano zinc mineral sunscreen, moisturizer and primer. It helps prevent sunburn and skin cancer with its broad-spectrum SPF value of 15 or higher. The formula is fast-absorbing and blends into the skin, giving it a natural glow without leaving a white cast. It is suitable for all skin tones and types, can be worn alone or under makeup, and is fragrance-free, vegan, clean, and reef-safe. The product is distributed by LIVETINTED in Los Angeles, CA.*
* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.
