Product Images Lunesta

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 3 images provide visual information about the product associated with Lunesta NDC 68258-7048 by Dispensing Solutions, 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.

NDC 68258-7048-XX - NDC 68258 7048 XX Sepracor

NDC 68258-7048-XX - NDC 68258 7048 XX       Sepracor

This is a packaging label for Lunesta 2mg tablets manufactured for Sepracor Inc. in Marlborough, MA. The tablets are round, white, and film-coated, with the imprint S191. The bulk source National Drug Code (NDC) is 63402-0191-10, and the product number is 7048-X. Each tablet contains .2 mg of eszopiclone and can cause drowsiness. The medication should be dispensed with a medication guide and stored at 77°F. Lot number, the sample expiration date, and the RX number are provided. The label includes a warning not to transfer the drug to anyone for whom it was not prescribed, and to keep it away from children. Finally, it includes information about the packager, Dispensing Solution.*

NDC 68258-7049-XX - NDC 68258 7049 XX Sepracor

NDC 68258-7049-XX - NDC 68258 7049 XX      Sepracor

This is a description of a medication called Lunesta 3 mg. The medication comes in a tight and light-resistant container. It is a dark blue, round, film-coated tablet that is for oral consumption. It is taken orally when needed or as directed. The medication may cause drowsiness and should be avoided with alcohol. The medication is habit-forming and should not be transferred to anyone else. The federal law prohibits drug transfer to anyone other than the patient for whom it was prescribed. The medication should be kept out of reach of children and stored at 77°F.*

Chemical Structure - lun00 0013 01

Chemical Structure - lun00 0013 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.