Product Images Rhus Tox
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Product Label Images
The following 3 images provide visual information about the product associated with Rhus Tox NDC 0220-4400 by Boiron, 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.
Rhus tox 30c is a homeopathic medicine made in France for joint pain that is better with motion. This product contains approximately 80 pellets of 0.443mg of the active ingredient per pellet. For adults and children, dissolve 5 pellets under the tongue 3 times a day at the onset of symptoms, until symptoms are relieved or directed by a doctor. If pregnant or breastfeeding, ask a health professional before using, and if symptoms persist for more than three days or worsen, stop use and consult a doctor. Keep out of reach of children. The drug facts show lactose and sucrose as inactive ingredients, and a link to BoironUSA.com/info for homeopathic dilutions details. If the pellet dispenser seal is broken, do not use. For any questions or comments, contact BoironUSA.com [email protected] or 1-800-BOIRON-1 (1-800-264-7661).*
Rhus toxicodendron 30c is a homeopathic medicine made in France that helps with joint pain that is improved by motion. Each box contains around 80 pellets with drug facts and instructions for use on the reverse. Dissolve 5 pellets under the tongue at the onset of symptoms until relieved or according to a doctor's directions. Keep out of reach of children and do not use if the pellet dispenser seal is broken. For more information, visit BoironUSA.com or contact Boiron Inc. in Newtown Square, PA.*
This product seems to be a joint pain relief solution that helps with painful joints, stiffness, and weather-related aches. Its main ingredient is Rhus Tox 30C, which is delivered in a "meltaway" form. Additionally, the product offers a free tube.*
* 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.