Product Images Sertraline Hydrochloride

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Product Label Images

The following 3 images provide visual information about the product associated with Sertraline Hydrochloride NDC 71205-047 by Proficient Rx Lp, 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.

71205 047 30

71205 047 30

This is a description of Sertraline Hydrochloride USP equivalent to Sertraline 100 mg, a medication used to treat depression and certain types of anxiety. It comes in the form of yellow colored, round biconvex, film coated tablets, debossed with "S3" on one side and breakline on the other side. The tablets are packaged in a bottle with 90 tablets per bottle. The medication guide should be provided separately with the dispensed product. It is manufactured by Intas Pharmaceuticals Limited in Ahmedabad, India, and packaged by Proficient Rx LP in Thousand Oaks, CA. The product should be stored at 25°C (77°F) and kept out of the reach of children. The lot number is 00000, and the expiration date is 00/00/00.*

71205-028-90 - sertraline 50mg 30

71205-028-90 - sertraline 50mg 30

This is a prescription drug called Sertraline HCI 50mg, supplied in a pack of 60 tablets. The tablets are light blue to blue colored, round, biconvex, and film-coated, with "S2" debossing on one side and a break line on the other. The medication guide needs to be dispensed separately. The tablets contain Sertraline hydrochloride equivalent to Sertraline 50mg. The product ID is QS002860. The manufacturer is Intas Pharmaceuticals Limited located in Ahmedabad, India. The medication should be stored at 25°C (77°F) and kept out of the reach of children. The lot number is 00000, and the expiry date is 00/00/00. The tablets are packaged by Proficient Rx LP located in Thousand Oaks, CA.*

Chemical Structure - sertraline str

Chemical Structure - sertraline str

* 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.