Product Images Loreal Paris Ever Pure Dandruff Scalp Care And Detox

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The following 2 images provide visual information about the product associated with Loreal Paris Ever Pure Dandruff Scalp Care And Detox NDC 49967-056 by L'oreal Usa Products Inc, 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 of a label - LOEverPure1

image of a label - LOEverPure1

This is a sulfate-free Pyrithione Zinc Dandruff Shampoo that cleanses and removes buildup while remaining gentle on color-treated hair and the scalp. It contains menthol and neem leaf extract to invigorate the scalp and leave it feeling fresh for up to 24 hours. The shampoo is gentle on the scalp and helps prevent recurrence of scalp flaking and itching associated with dandruff. It should be used at least twice a week or as directed by a doctor, avoiding contact with the eyes. It comes in a bottle of 8.5 fl oz (250 ml). Inactive ingredients include water, cocamidopropyl betaine, and sodium lauroyl sarcosinate, among others. The product is cruelty-free and made using eco-friendly processes.*

image of a label - LOEverPure2

image of a label - LOEverPure2

EverPure Scalp Care + Detox Shampoo is a sulfate and harsh salts free formula that is designed to clean, relieve, and provide special care for color-treated hair. Its formula is enriched with menthol and neem leaf extract ingredients that provide a gentle, purely sensorial lather, and a fresh aromatic scent. The shampoo is also effective in removing dirt, dandruff, flakes, and oil while remaining gentle on colored hair. Inactive ingredients in this shampoo include cocamidopropy hetaine, sodium hydroxide, and glycol distearate. However, it is essential to avoid contact with the eyes during use of the product. For best results, the shampoo should be used at least twice a week or as directed by a doctor.*

* 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.