Product Images Benzonatate

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 3 images provide visual information about the product associated with Benzonatate NDC 10544-123 by Blenheim Pharmacal, 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.

Label - LABEL BENZONATATE CAPS 100MG BPI(10544 129 09) ASCEND(67877 105 05) REV2

Label - LABEL BENZONATATE CAPS 100MG BPI(10544 129 09) ASCEND(67877 105 05) REV2

This is a description of the prescription drug Benzonatate, which comes in the form of capsules containing 100mg of USP. The National Drug Code (NDC) is 10544-129-09. The lot numbers, expiration dates and dosage information are included for the product. It should be stored at room temperature, away from light in a light-resistant container. It is repackaged by Bl at North Blenheim NY 12131 and distributed by Ascend Laboratories, LLC in Monivale, NJ 07845. This is a prescription drug for which only a doctor can provide the dosage. There seems to be some errors in the text.*

Label - LABEL BENZONATATE CAPS 200MG BPI(10544 123 20) ASCEND(67877 106 05) REV2

Label - LABEL BENZONATATE CAPS 200MG BPI(10544 123 20) ASCEND(67877 106 05) REV2

Benzonatate Capsules, USP is a medication used for cough relief. Each capsule contains 200mg of the active ingredient. This product has been manufactured by Ascend Laboratories LLE and packaged by Blenheim Pharma. It is important to store the capsules at controlled room temperature and in a container that is kept out of reach of children. The recommended dosage can be found in the package insert. The lot number for this product is BPO0DO00D and the expiration date is 00/00/0000. There are additional variations of this product with different NDC and MFG numbers, lot numbers and expiration dates.*

Structure - structure

Structure - structure

* 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.