Product Images Lisinopril
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 4 images provide visual information about the product associated with Lisinopril NDC 33261-332 by Aidarex Pharmaceuticals 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.
Lisinopril USP - lisinopril 10mg 30mg 40mg tab for lupin 1
IMAGE LABEL - lisinopril 10mg 30mg 40mg tab for lupin 2
This is a medication called Lisinopril produced by Aidarex Pharmaceuticals LLC and manufactured by Lupin Limited in India. It is a generic version of Zestril, prescribed to treat high blood pressure. The tablets are pink with "10" imprinted on them, and each bottle contains 30 tablets. The package insert must be read before use, and the medication should not be dispensed without a prescription. It should also be kept out of reach of children and stored at controlled room temperature. Dosage instructions are provided in Spanish.*
IMAGE LABEL - lisinopril 10mg 30mg 40mg tab for lupin 3
This text is related to a medication named "Lisinopril" manufactured by the company "AIDAREX PHARMACEUTICALS LLC". The medication is available in 30mg strength and comes in a container with 307 tablets. It also mentions another similar medication called "Zestril." There are several product codes provided for the medication, but further information is not available due to the text being poorly extracted.*
IMAGE LABEL - lisinopril 10mg 30mg 40mg tab for lupin 4
This is a description of Lisinopril, a generic drug for Zestril used for managing high blood pressure. Available in 40mg tablets, it has "LSRRI somg a0" and "GENERIC FOR: ZESTRIL NUC e" written on it. The manufacturer mentioned is Lupin Limited based in India. The text also includes RX and NDC codes, but no dosage information is given. The rest of the text seems to be gibberish.*
* 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.