Folliculinum Pellet
Product Images NDC 0220-2129

Product Visual Gallery

This gallery contains 3 technical images submitted to the FDA as part of the official labeling for Folliculinum (NDC 0220-2129). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.

As provided by Boiron, these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.

FDA Label Image

Label (2nd Panel)

This appears to be the text from a label of a medication product. It states the drug facts and mentions the inactive ingredients. It also provides contact information for the company. The text makes reference to homeopathic solutions. However, it is not clear what the medication is for.*

FDA Label Image

Label (3rd Panel)

This is a Drug Facts label for a product with an active ingredient indicated on the front. The label provides information on the recommended uses, dosage, warnings, and precautions for the product. It advises users to consult a health professional before use if pregnant or breastfeeding and to keep it out of reach of children. The recommended directions suggest dissolving 5 pellets under the tongue, 3 times a day until symptoms are relieved or as directed by a doctor. It also reminds users not to use the pellets if the seal of the dispenser is broken.*

FDA Label Image

Label (Folliculinum6c)

This is a description of a homeopathic medicine called Folliculinum 6¢. It is made in France by Boiron and comes with a packet containing around 80 pellets. The medicine is intended to relieve discomfort and aches associated with PMS*. The medicine is approved by HPUS and has the NDC number 0220212941. The description also mentions a lot number and expiration date but these are not readable. The last line appears to contain non-English characters and is not understandable.*

* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.