Product Images Escitalopram Oxalate
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 4 images provide visual information about the product associated with Escitalopram Oxalate NDC 70518-1697 by Remedyrepack 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.
Escitalopram 10mg 70518 1697 01
This is a medication label for "ESCItalopram" tablets, with a strength of 10 mg and a quantity of 30 tablets. The medication is sourced from Torrent Pharmaceuticals in Bharuch, India. The directions for use can be found in the package insert. The medication should be stored at 20-25°C (58-77°F) with excursions permitted to 15.30°C (59-86°F). It is important to keep this medication out of the reach of children.*
Escitalopram 10mg 70518 1697 02
This is a description of Escitalopram, a medication available in 10 mg tablets with a quantity of 60 tablets. It is a prescription (RX ONLY) drug with the NDC #70518-1697-02 and manufactured by Torrent in Bharuch, India. The medication should be stored between 20-25°C (58-77°F) with excursions permitted to 15.30°C (59-86°F) according to USP standards. The packaging information also includes a repackager: RemedyRepack inc., located in Indiana, PA 15701. It is important to keep this medication out of the reach of children. For specific usage instructions, refer to the package insert.*
Remedy_Label - Remedy Label
This is a medication information for Escitalopram, with a dosage of 10 mg per tablet and quantity of 30 tablets. The medication is manufactured by Torrent in Bharuch, India. It should be stored between 20-25°C (58-77°F) with allowable excursions to 15.30°C (59-86°F). The medication is repackaged by Remedy Repack Inc. in Indiana. Please refer to the package insert for dosage instructions and other relevant information.*
afe9596b 3231 4248 891c 5f2f9e6dd83a 01
* 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.
