Product Images Montelukast

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 5 images provide visual information about the product associated with Montelukast NDC 68001-361 by Bluepoint Laboratories, 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.

montelukast 30s

montelukast 30s

Montelukast Sodium Tablets, USP is a prescription drug used for adults 15 years and older as per the usual dosage described in the prescribing information. The package consists of 30 film-coated tablets containing Montelukast sodium USP 10.4 mg equivalent to Montelukast 10 mg. The medication guide should be dispensed to each patient by the pharmacist. It is manufactured by Macleods Pharmaceuticals Ltd. in Baddi, Himachal Pradesh, India, and is distributed by BluePoint Laboratories. The tablets should be stored at 20°C to 25°C and protected from moisture and light.*

montelukast 500s

montelukast 500s

This is a description of a medication. The tablet contains Montelukast sodium, USP 10.4 mg, which is equivalent to Montelukast 10mg. It is intended for adults who are 15 years of age and older. The prescribing information should be consulted for usual dosage. The tablets should be stored at 20° to 25°C. The medication should be dispensed by a pharmacist and kept in a well-closed, light-resistant container to protect it from moisture and light. The original package should be used to store the medication and it should be kept out of reach of children. The manufacturer is Macleods Pharmaceuticals Ltd. with a code number of HP/152/07. The number of tablets in the container is 500.*

montelukast 90s

montelukast 90s

montelukast-fig-1 - montelukast fig 1

montelukast-fig-1 - montelukast fig 1

montelukast-structural - montelukast structural

montelukast-structural - montelukast structural

* 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.