Product Images Hydrastis Canadensis

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Product Label Images

The following 2 images provide visual information about the product associated with Hydrastis Canadensis NDC 0220-2558 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.

label - HYDCAN12X

label - HYDCAN12X

Hydrastis canadensis is a homeopathic medication made in France. It contains 0.443 mg of an active ingredient per pellet and is designed to relieve symptoms of post-nasal drip. The medication should be dissolved under the tongue three times a day until symptoms disappear or until a doctor directs otherwise. There are warnings for consumers to ask a healthcare professional before use if pregnant or breastfeeding and to stop using the medication and speak with a doctor if symptoms persist for more than three days or worsen. The medication contains lactose and sucrose but is free of additional active ingredients. The product is distributed by Boiron Inc. in Newtown Square, PA, and can be had by twisting the cap until five pellets are dispensed at which point patients can then remove the cap and pour the pellets under the tongue. More information on the homeopathic dilutions used can be found on boironusa.com.*

Hydrastis canadensis 12X label

Hydrastis canadensis 12X label

This is a medication label for a homeopathic medicine made in France, containing Hydrastis canadensis for the treatment of post-nasal drip. It contains 80 pellets with less than 10 mg of hydrastine and berberine alkaloids per pellet. It provides drug facts, warnings, and instructions for use, including dissolving 5 pellets under the tongue 3 times a day or following a doctor's directions. It also informs on inactive ingredients and advises not to use if the pellet dispenser seal is broken. Contact information for Boiron Inc., the distributor, is also provided.*

* 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.