Inspra Tablet, Film Coated
Product Images NDC 58151-142
View Photos of Packaging, Regulatory Labels, and Product Appearance
Product Visual Gallery
This gallery contains 7 technical images submitted to the FDA as part of the official labeling for Inspra (NDC 58151-142). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.
As provided by Viatris Specialty Llc, these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.
Figure 1 (Image 02)
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Figure 2 (Image 05)
This text provides information related to total number of events, patients, demographics (age, gender, race), medical history (diabetes, hypertension), Killip Class, creatinine clearance, use of medications (beta blockers, ACE inhibitors, Digoxin, diuretics), and a comparison of outcomes between Eplerenone group and Placebo group with the Hazard Ratio and 95% Confidence Interval.*
Ndc 58151-142-93 (Image 06)
This text provides information about eplerenone tablets, a medication used for certain heart conditions. The tablets are to be stored at a temperature range of 15-30°C (50-86°F) and dispensed in child-resistant containers. Each tablet contains 25 mg of eplerenone. For more details on dosage and use, refer to the accompanying prescribing information. The product is distributed by Viatris Specialty LLC from Morgantown, WV 26505 USA.*
Ndc 58151-143-93 (Image 07)
This text appears to be a label for medication called INSPRA, containing eplerenone tablets with a dosage of 50 mg. It provides storage instructions, NDC number, and the distributor information as Viaris Specialty LLC. The medication should be stored at 25-30°C (59-86°F) temperature range. It is available in child-resistant containers and comes in 30 tablet packs. For full prescribing information, further details are available.*
* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.