Product Images Dragon Pain Relieving
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Product Label Images
The following 2 images provide visual information about the product associated with Dragon Pain Relieving NDC 83552-119 by Americanna Wellness, 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.
1 - 83552 119 00 Dragon 3.4 Lotion Xtra Broad Spectrum CARTON
Dragon Pain Relieving Lotion is a powerful and effective solution for soothing joints, muscles, and minor pain. Formulated with ancient herbs, terpenes, and cannabinoids, this lotion provides fast relief for aches and pains. It contains active ingredients like Menthol and Camphor, which provide a topical analgesic effect. This lotion is specifically designed to temporarily relieve minor aches and pains associated with muscle strains, arthritis, bruises, and sprains. It should be applied to the affected area up to 3 to 4 times daily, and caution should be taken to avoid contact with the eyes or bandaging tightly. This lotion is for external use only and should not be used on open wounds or damaged skin. If symptoms persist or worsen, medical advice should be sought. It is recommended to consult a doctor before using the lotion if pregnant or breastfeeding. The lotion is manufactured by Canna Wellness Inc. in Bellingham, WA and more information can be obtained on their website or by calling their customer service line.*
2 - 83552 119 00 Dragon 3.4 Lotion Xtra Broad Spectrum INNER
XTRA STRENGTH BROAD SPECTRUM Menthol 11% | Camphor 10%. Bioavailability is 2% faster with Dragon pain relief emulsified cannabinoids. Dragon is a powerful solution formulated with menthol and camphor that effectively soothes joints, muscles, backaches, stiffness, and minor pains. For external use only. Manufactured by Americanna Wellness Inc. at 1788 Midway Lane, Bellingham, WA 98226. Visit americannawellness.com for more information.*
* 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.
