Product Images Losartan Potassium And Hydrochlorothiazide

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Product Label Images

The following 4 images provide visual information about the product associated with Losartan Potassium And Hydrochlorothiazide NDC 63187-599 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.

63187-599-30 - losartanhctz fig1

63187-599-30 - losartanhctz fig1

This is a medication package of Losartan Potassium and Hydrochlorothiazide tablets, each containing 50mg and 12.5mg respectively. The tablets are oval shaped, yellow colored, and film-coated with beveled edges. They are packaged in a set of 30 and are debossed with 'E' on one side and '48' on the other. The medication is manufactured by Aurobindo Pharma Limited Unit-VII in India and packed by Proficient Rx LP from Thousand Oaks, CA 91320. The package mentions the lot number, expiration date, and storage instructions. The NDC number for the package is 63187-599-30.*

63187-602-90 - losartanhctz fig5

63187-602-90 - losartanhctz fig5

This is a bottle of Losartan Potassium 100mg/HCTZ 25mg tablets manufactured by Aurobindo Pharma Limited in Mahaboob Nagar, India. The bottle contains 90 yellow, oval-shaped, film-coated tablets with a beveled edge. Each tablet is imprinted with "€" on one side and "49" on the other. The tablets are used for treating hypertension (high blood pressure). The bottle should be stored at room temperature (20°-25°C or 68°-77°F) and kept out of the reach of children. The lot number is 00000, and the expiration date is 00100100. The product is packaged by ProficientRx LP of Thousand Oaks, CA.*

Losartan Potassium Chemical Structure - losartanhctz str1

Losartan Potassium Chemical Structure - losartanhctz str1

Hydrochlorothiazide Chemical Structure - losartanhctz str2

Hydrochlorothiazide Chemical Structure - losartanhctz str2

* 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.