Product Images Aesculus Hippocastanum

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Product Label Images

The following 2 images provide visual information about the product associated with Aesculus Hippocastanum NDC 63545-760 by Hahnemann Laboratories, 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.

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9cd5908e e058 30af e053 2a95a90a2c41

Hahnemann Labs Inc is located in San Rafael and produces homeopathic medicines. The active ingredient in this particular medicine is Aesculus Hippocastanum LM1, intended for traditional homeopathic uses such as for headaches. The product is in pellet form with a net weight of 30g and contains sucrose as an inactive ingredient. A warning label advises to consult a health professional if symptoms persist beyond three days, and to not use if pregnant or nursing. The product can be taken orally as directed by a health professional. An emergency contact number is also provided. The unreadable text at the end is not useful for description.*

AESCULUS HIPPOCASTANUM LM1 30g - AESCULUS HIPPOCASTANUM LM1 30g

AESCULUS HIPPOCASTANUM LM1 30g - AESCULUS HIPPOCASTANUM LM1 30g

This is a description of a homeopathic medicine called AESCULUS HIPPOCASTANUM LM1 by Hahnemann Labs Inc. The product comes in a container weighing 30g of pellets and is intended for traditional homeopathic uses for headache. The active ingredient and inactive ingredient used in the medicine are not specified. The medicine should not be used by pregnant or breastfeeding individuals without consulting a health professional. If any symptoms persist for more than 3 days, a health professional should be consulted. The oral dose is 5 pellets, which should be taken once, or as directed by a health professional. The customer service number of the manufacturer is also given. The text at the end is not-readable.*

* 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.