Product Images Coola Classic Body Sunscreen Guava Mango Spf 50

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The following 2 images provide visual information about the product associated with Coola Classic Body Sunscreen Guava Mango Spf 50 NDC 21839-450 by Gordon Laboratories, 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.

Classic Body Sunscreen Guava Mango Tube 148 mL - Classic Body Sunscreen Guava Mango Tube 148 mL

Classic Body Sunscreen Guava Mango Tube 148 mL - Classic Body Sunscreen Guava Mango Tube 148 mL

This is a description of an organic COOLA Classic Body Sunscrean Lotion SPF 50 designed for use every day, with broad-spectrum coverage, water resistance, and added plant protection that includes natural oils to hydrate and nourish the skin. The formula is fortified to protect the skin while remaining light and sheer. The lotion includes Avobenzone 1.75%, Homosalate 5.0%, Octisalate 2.0%, Octocrylene 5.0% as active ingredients. The product is made in the USA using thoughtfully sourced global ingredients.*

Classic Body Sunscreen Guava Mango carton 148 mL - Classic Body Sunscreen Guava Mango carton 148 mL

Classic Body Sunscreen Guava Mango carton 148 mL - Classic Body Sunscreen Guava Mango carton 148 mL

This product is a sunscreen lotion that decreases the risk of skin cancer and early skin aging caused by the sun by utilizing plant-based ingredients such as Buriti oil, Meadowfoam Seed Oil, Raspberny Seed Oil, and Prickly Pear extract. It has a sun protection factor (SPF) of 50 with water-resistant properties that lasts up to 80 minutes. The product is to be applied generously 15 minutes before sun exposure and should be reapplied every two hours. It also includes warnings not to use on damaged skin, keep away from the eyes and to limit stay in the sun especially from 10 am to 2 pm. There is a contact number available for questions or concerns.*

* 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.