Product Images Anti-dandruff

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Product Label Images

The following 2 images provide visual information about the product associated with Anti-dandruff NDC 83080-121 by Meeray Cosmetics Co., Ltd., 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.

Ecocare 32oz - Ecocare 1000mL

Ecocare 32oz - Ecocare 1000mL

This is a description of a dandruff shampoo that contains an active ingredient designed to treat and prevent itching, flaking, and scaling of the scalp caused by dandruff or seborrhea. It also gently cleanses and prevents dryness. The shampoo is part of the HNC (Hair Nutrition Campler) series, which aims to nourish the scalp and hair, and restore a healthy condition. The product is paraben, sulfate, DEA/MEA, and wheat-free with no phthalates. It comes in a 32 fl. oz. bottle, and it is meant for external use only. The user should avoid contact with the eyes, rinse thoroughly if contact occurs, and consult a physician if the condition worsens or does not improve. The shampoo should be shaken well, applied to wet hair, massaged onto the scalp, and rinsed thoroughly for best results. The ingredients list includes a variety of natural extracts and oils such as soybean oil, coconut oil, and thyme oil. The shampoo is distributed by Meray Cosmetics Co. Ltd, and it is made in the USA.*

Ecocare 10oz - Ecocare 300mL

Ecocare 10oz - Ecocare 300mL

This is a drug facts label and description of a dandruff shampoo. It contains zinc pyriona to help prevent flaking and scaling of the scalp caused by dandruff. The active ingredient is Farposs. This product is sulfate-free, wheat-free, and paraben-free. The label also provides directions for use and warnings, including information on what to do if the product accidentally enters the eyes. The ingredients list mentions several substances such as guar, soybean, and coconut.*

* 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.