Valsartan Tablet, Film Coated
Product Images NDC 71205-301

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Product Visual Gallery

This gallery contains 3 technical images submitted to the FDA as part of the official labeling for Valsartan (NDC 71205-301). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.

As provided by Proficient Rx Lp, these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.

FDA Label Image

71205-301-90 (Valsartan 320mg 90s Legacy)

71205-301-90 (Valsartan 320mg 90s Legacy)
This is a prescription drug called Valsartan with a strength of 320mg. The product contains 90 tablets that are biconvex, oval-shaped, and unscored with a dark grey-violet color. It is manufactured by Macleods Pharmaceuticals Ltd. in Daman (U.T.) INDIA and has the product ID of SV030190. The tablets should be stored at room temperature (20°-25°C or 68°-77°F) and kept out of reach of children. The lot number is 00000 with an expiration date of 00/00/00, and the SN number is MASTER. The drug comes in blister packs and has NDC code 71205-301-90. The drug was relabeled by Proficient Rx LP in Thousand Oaks, CA 91320.*
FDA Label Image

111 (Valsartan Figure1)

111 (Valsartan Figure1)
This is a table showing the subgroups of patients involved in a clinical study comparing Valsartan to Captopril. The first column lists the subgroups and the second column shows the percentage of patients in that subgroup. The subgroups include all patients, those who are under 65 years old, male and female patients, Caucasians and non-Caucasians, patients from the US and those from outside of the US, and patients who did or did not take beta-blockers. The table also includes the results of the study: Valsartan was favored over Captopril at 5, 10, and 15 time points.*
FDA Label Image

Valsartan (Valsartan Structural Formula)

* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.