Product Images Felbamate

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Product Label Images

The following 4 images provide visual information about the product associated with Felbamate NDC 51525-0430 by Wallace Pharmaceuticals 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.

Felbamate Structural Formula - image 01

Felbamate Structural Formula - image 01

Felbamate 400 mg Tablets Bottle Label - image 02

Felbamate 400 mg Tablets Bottle Label - image 02

This is a description of a medicine named Felbamate BS, in the form of tablets of 400mg. The manufacturer is Wallace Pharmaceuticals, Inc. located in Somerset, NJ. The medicine comes in a container containing 100 tablets and the product's expiration date is not readable. The product has a National Drug Code number 51525-0430-1 and a lot number LB-032010-04, revised in May 2018.*

Felbamate 600 mg Tablets Bottle Label - image 03

Felbamate 600 mg Tablets Bottle Label - image 03

This is a description of a medication identified by NDC 51525-0431-1. The medication is Felbamate, in tablet form, and each tablet contains 600 mg. The pack contains 100 tablets and has the inscription "B only" on it. The manufacturer is indicated as Wallace Pharmaceuticals, based in Somerset, NJ, with the production date indicated as LB-032110-04, Rev. 5/2018. Further details such as expiration date and LOT number are also present.*

Felbamate 8 fl oz (237 mL) Oral Suspension Bottle Label - image 04

Felbamate 8 fl oz (237 mL) Oral Suspension Bottle Label - image 04

This is a medication for Felbamate Oral Suspension, used to treat seizures. It comes in a bottle of 81 fluid ounces (237 mL), contains 5 mL of the medication which consists of 600 mg of felbamate. The medication should be shaken before use. The additional text may refer to product ID and expiration date, but not much can be understood from the output.*

* 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.