Bm Bm240 Drops Liquid
Product Images NDC 85816-2240

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Product Visual Gallery

This gallery contains 2 technical images submitted to the FDA as part of the official labeling for Bm Bm240 Drops (NDC 85816-2240). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.

As provided by Bm Private Limited, 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

Bm240 2 (Bm No 240 2)

Bm240 2 (Bm No 240 2)
This is a homoeopathic product known as "Agrimonia Compound" designed to support the relief of symptoms related to chronic gynaecological infections. The product contains active ingredients like Agrimonia, Arsenic album, Hydrastis can, Kali bich, Kreosotum, Graphite, Cimicifuga, and Nitricum acidum. The recommended dosage is 10-15 drops, 3-4 times a day in water. It is advised to keep the product away from children and store it in a cool and dry place. This product is manufactured in Pakistan by BM Homoeopathic Pharmaceuticals, with market authorization held by Bestmade Natural Products in the USA. For more information, refer to the enclosed package information leaflet.*
FDA Label Image

Bm240 (Bm No 240)

Bm240 (Bm No 240)
Agrimonia Compound is a homoeopathic product with active ingredients such as Agrimonia, Arsenic album, Hydrastis can, Kali bich, Kreosotum, Graphite, Cimicifuga, and Nitricum acidum. It is designed to provide support in relieving symptoms of chronic gynaecological infection. The product is manufactured by BM Homoeopathic Pharmaceuticals in Lahore, Pakistan, and distributed by Bestmade Natural Products in the USA. It is recommended to take 10-15 drops of the product, 3-4 times a day, mixed in water. Keep away from children and store in a cool, dry place. For more information, refer to the enclosed package leaflet.*

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