Product Images Good Neighbor Mineral Oil Laxative
View Photos of Packaging, Labels & Appearance
- Remove protective shield illustration - 9788c057 665e 4352 b03a 022259e5ae76 01
- Left Side position illustration - 9788c057 665e 4352 b03a 022259e5ae76 02
- Knee-chest position illustration - 9788c057 665e 4352 b03a 022259e5ae76 03
- Good Neighbor Pharmacy Mineral Oil Enema box principal display panel - 9788c057 665e 4352 b03a 022259e5ae76 04
- Good Neighbor Pharmacy Mineral Oil Enema box side and back - 9788c057 665e 4352 b03a 022259e5ae76 05
Product Label Images
The following 5 images provide visual information about the product associated with Good Neighbor Mineral Oil Laxative NDC 46122-600 by Amerisource Bergen, 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.
Good Neighbor Pharmacy Mineral Oil Enema box principal display panel - 9788c057 665e 4352 b03a 022259e5ae76 04

This is a description of a ready-to-use enema product manufactured by a company named Goop Neighbor Pharmacy. This enema is designed to relieve occasional constipation and contains mineral oil as its active ingredient. The lubricated tip of this enema is comfortable to use and works within minutes. The product comes in a box that has tamper seals for safety. The product contains sodium-free lubricant. This text has some errors and does not contain any non-English characters.*
Good Neighbor Pharmacy Mineral Oil Enema box side and back - 9788c057 665e 4352 b03a 022259e5ae76 05

This is a set of instructions on how to use a mineral oil enema for the relief of occasional constipation. The label contains important information, such as the product name, its features, and dosage information. It also includes some positional advice, such as that this enema works best when used in the left side position or the knee-chest position.*
* 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.