Product Images Feel Good Labs Natural Pain

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Product Label Images

The following 2 images provide visual information about the product associated with Feel Good Labs Natural Pain NDC 70554-260 by The Feel Good Lab, 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.

Label - Label

Label - Label

This is a description of a topical analgesic called "DT THE FEEL GOOD", which contains Menthol 1.25% as its active ingredient. It is indicated for temporary relief of minor aches and pains of muscles and joints associated with arthritis, simple backache, sprains, bruises, and strains. Features of the product include external use only, avoidance of contact with eyes, no applicability to wounds or damaged skin, and consultation with a physician if symptoms persist for more than seven days. It also includes a long list of other natural ingredients. The product is available in a 100 ml/3.4 fl. oz. container.*

Label2 - Label2

Label2 - Label2

This is a drug guide for the Feelgood Natural Pain Cream, a topical analgesic used for temporary relief of minor aches and pains associated with arthritis, back pain, sprains, bruises, and strains. The drug contains 100% natural ingredients, such as Yarrow Extract, Aloe Vera Gel, Turmeric Root Extract, and Glucosamine. It also has other medicinal ingredients like Amica Montana, Boswellia Myristoleate, and Chondroitin Sulfate. The drug must be applied to the affected area not more than three to four times per day by adults and children, two years and older. Children under two years should consult a physician. The Feelgood Natural Pain Cream packaging has caution and safety information, such as avoiding contact with eyes, not applying to damaged skin, and keeping out of reach of children. If symptoms persist for more than seven days or ingested, a physician must be consulted.*

* 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.