Product Images Lisinopril And Hydrochlorothiazide
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Product Label Images
The following 5 images provide visual information about the product associated with Lisinopril And Hydrochlorothiazide NDC 0591-0862 by Actavis Pharma, 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.
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This is a drug label for Lisinopril and Hydrochlorothiazide Tablets, USP in the pack size of 100 tablets, with 10 mg/12.5 mg strength, manufactured by Watson Pharma Private Limited in India and distributed by Actavis Pharm, Inc. It is meant for prescription use only and dispense in a tight, light-resistant container. The prescribing information is available in the package outsert. It should be stored at 20° to 25°C (68” to 77°F) and protected from excessive light and humidity. LOT/EXP and other important details are provided on the label.*
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NDC 0591-0861-01 is a medication that contains lisinopril and hydrochlorothiazide. The tablets are stored in a light-resistant container, and should be protected from excessive light and humidity. They were manufactured in India by Watson Pharrma Private Limited and distributed in the US by Actavis Phama, Inc. Full prescribing information is available.*
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This is a description of Lisinopril and Hydrochlorothiazide Tablets manufactured by Watson Pharra Private Limited in India and distributed by Actavis Pharma, Inc in the USA. Each tablet contains Lisinopril 20 mg and Hydrochlorothiazide 25 mg. These are prescription drugs packaged in a tight, light-resistant container and should be kept at 20° to 25°C (68° to 77°F) to protect from excessive light and humidity. More information is provided in the package outsert. The text includes the NDC number, manufacturing, and distribution information. LOT/EXP information and a serialization coding area are also provided.*
* 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.