Product Images Sertraline

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 3 images provide visual information about the product associated with Sertraline NDC 55154-3570 by Cardinal Health 107, Llc, 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.

image-1 - 78d3579a 260f 4bb2 95f2 8ee8a60fae18 01

image-1 - 78d3579a 260f 4bb2 95f2 8ee8a60fae18 01

Bag Label - FD8A815E 88B7 4BEF 9E32 6DBC735711A3 00

Bag Label - FD8A815E 88B7 4BEF 9E32 6DBC735711A3 00

This is a pack of 10 tablets of Sertraline Hydrochloride, USP 100mg each, manufactured in Goa, India, by Lupin Limited, for Lupin Pharmaceuticals, Inc which is distributed in the United States by Major® Pharmaceuticals and Cardinal Health. It contains warnings regarding child-resistant package and storage temperature. It is indicated to see product insert for prescribing and further warnings.*

Bag Label - FD8A815E 88B7 4BEF 9E32 6DBC735711A3 01

Bag Label - FD8A815E 88B7 4BEF 9E32 6DBC735711A3 01

This is a description of Sertraline Hydrochloride Tablets USP 50 mg manufactured by Lupin Limited in Goa, India. Each film-coated tablet contains 50 mg of sertraline, which is used for treating depression, anxiety, obsessive-compulsive disorder, and other mental health disorders. The tablets come in a 10-tablet unit dose package that is not child-resistant and intended for institutional use only. The medication should be kept out of the reach of children. The package insert advises on prescribing information, precautions, and warnings. The medication should be stored at 20° to 25° C (88" to 77 F). A medication guide is available at www.majorpharmaceuticals.com. The product is distributed by Major Pharmaceuticals in Livonia, Michigan, and Cardinal Health in Dublin, Ohio. The code number is GO/DRUGS/654, and it is available by prescription only.*

* 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.