Product Images Complexion Clear Acne Treatment Rejuvenating

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Product Label Images

The following 2 images provide visual information about the product associated with Complexion Clear Acne Treatment Rejuvenating NDC 42876-003 by Results Rna, Llc, 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.

Label1 - Label1

Label1 - Label1

This is a drug facts label for a benzoyl peroxide 2.5% cream for the treatment of acne. It warns against using it near eyebrows and hair as it may lighten hair color. It advises against using the product for those with very sensitive skin or those who are sensitive to benzoyl peroxide. The label also recommends avoiding sun exposure and contact with eyes, lips, and mouth when using the cream. It is manufactured by a company called Complexion Clear, located in Utah. Patent pending.*

Label2 - Label2

Label2 - Label2

This is a drug information label for a product used for acne treatment. The product should be kept away from dyed fabrics and excessive skin irritation may occur, leading to redness, burning, itching, peeling or swelling. To prevent skin irritation, the product should be used sparingly with lower concentration. Using acne medication simultaneously may pose a risk of skin irritation and dryness, and only one product should be used at a time. The user should stop the use of the product if the irritation becomes severe. The product is to be applied on the affected area of the skin once or thrice daily after cleaning with gradual increase in frequency. The product may cause dryness, and sunscreen is recommended during outdoor activities. The product should not be used if skin irritation develops. The product contains glutathione, aloe vera, glycerin, advanced cellular silver, and carbomer as inactive ingredients. For any questions, the number provided on the label should be contacted.*

* 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.