Product Images Real Relief
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 5 images provide visual information about the product associated with Real Relief NDC 65808-320 by Gmp Laboratories Of America, 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.
This product is a homeopathic medicine aimed at relieving asthma and respiratory symptoms. The active ingredients are natural and listed as Eriodictyon Californicum, Histaminum, Ipecacuanha, Lobelia Inflata, Sambucus Nigra, and Solidago Virgaurea. It comes in a package of 30 chewable tablets, and adults and children over 12 years can use it. Users should not take it with food, but instead chew the tablets and dissolve them in the mouth. The recommended dose is four times daily, and users are encouraged to reduce the intake with improvement. The directions warn not to use if the seal is broken or missing and to store at room temperature. The information on the product's label is based on traditional homeopathic practice, which may not have been evaluated by the FDA. If symptoms persist for more than seven days, users should consult a doctor. The product also comes with an instruction in the carton.*
This is a product label for a homeopathic medicine indicated for respiratory care and symptom relief. It claims to aid in gasping for air, coughing, difficulty breathing, excess mucus, and chest congestion. The product is chewable, and complete instructions are included in the carton.*
This appears to be a description of a homeopathic medicine for respiratory care, specifically for symptoms related to ear, asthma, gasping for air, wheezing, difficulty breathing, coughing, and excess mucus. The text is partially incomplete and contains some random characters, but this is the best possible interpretation given the text 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.