Product Images Hempvana Ultra Strength Pain Relief Cream

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Product Label Images

The following 2 images provide visual information about the product associated with Hempvana Ultra Strength Pain Relief Cream NDC 73287-016 by Telebrands Corp, 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 - Hempvana PainCreamLine JarLabel Lidcoaine v5 OL page 001

1 - Hempvana PainCreamLine JarLabel Lidcoaine v5 OL page 001

Hempvina® is an ultra-strength pain relief cream that uses lidocaine and hemp seed oil to help people reduce pain in different parts of their body. The cream is designed to be used externally only and should be applied up to four times a day on affected areas. This cream should not be used if there are wounds or damaged skin. It's important to note that this cream should only be used as directed and the label should be followed accurately to avoid any allergic reactions. The cream has other ingredients such as sunflower seed oil, cetearyl alcohol, and more. Hempvina® is distributed by Telebrands Corp and comes with a tamper-evident safety seal.*

2 - Hempvana PainCreamLine JarLabel Lidcoaine v5 OL page 002

2 - Hempvana PainCreamLine JarLabel Lidcoaine v5 OL page 002

Hempvana is a pain relief product that combines the benefits of science with the moisturizing goodness of hemp seed oil. It aims to help alleviate pain and discomfort. The product should be applied generously to the affected area and massaged until absorbed. It should not be used on children under the age of 2 without consulting a physician. Hempvana contains Lidocaine as an active ingredient and is for external use only. The product should not be applied to wounds, damaged, broken, or irritated skin, or near eyes or mucous membranes. The package contains 8.8275 inches of product. Access additional information at Hempvana's website.*

* 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.