Product Images Broncochem Cold And Flu Caplets
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Product Label Images
The following 2 images provide visual information about the product associated with Broncochem Cold And Flu Caplets NDC 65131-101 by Laboratorio Magnachem International Srl, 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.
image descriptionBC&FBOX - Broncochem Cold and Flu Caplets Box 01
This is a detailed description of a medicine product labeled as "Broncochem." It is an antiviral tablet used to treat symptoms like congestion, runny nose, sneezing, itchy throat/nose, and watery eyes associated with allergies. The product contains active ingredients like Acetaminophen, Chlorpheniramine Maleate, Dextromethorphan HBr, and Phenylephrine HCL. It also provides warnings about liver damage, sore throats, overdose precautions, and advice on usage for specific health conditions. The product is non-drowsy and meant for adults and children over 12 years old. It contains instructions for use and contact information for medical guidance. The tablets are manufactured in the Dominican Republic for Global Corporation in the USA and are FDA registered.*
Broncochem Cold and Flu Package - PAPEL BRONCOCHEM COLD FLU 268.32mm R.2
This text appears to be a description of two different types of medicines: Broncochem Multi-Symptom Formula and Cold & Flu Caplets. Both products are non-drowsy and offer relief for symptoms such as bronchial congestion, respiratory irritation, nasal congestion, and allergy symptoms like sneezing and itchy eyes. The directions advise not to exceed 6 doses within a 24-hour period and provide specific dosage instructions based on age. The products are made in the Dominican Republic and contain various active and inactive ingredients to address different symptoms. For further information or questions, contact 1-561-338-5221 or visit www.broncochem.com.*
* 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.
