Product Images Sildenafil
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Product Label Images
The following 11 images provide visual information about the product associated with Sildenafil NDC 69097-953 by Cipla Usa 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.
This is a description for Sildenafil tablets with NDC 69097-953.02 R. The medication is used to treat male sexual function problems such as impotence or erectile dysfunction. Each film-coated tablet contains 100 mg of Sildenafil, USP, and it comes in a bottle with 30 tablets. The tablets should be stored at room temperature and dispensed in tight, light-resistant containers. The medication is manufactured by Appoo Pharma LLC in Piscataway, NJ, and distributed by Cipla USA, Inc. in Warton, NJ. The dosage and usage should be discussed with a healthcare professional.*
This is a prescription-only medication with a National Drug Code (NDC) of 69097-951-02. It contains Sildenafil, USP and comes in a box with 30 film-coated tablets. The tablets should be stored in a tight container at room temperature between 15-30°C (59-86°F). The dosage and usage instructions are provided in an accompanying prescribing information leaflet. The manufacturer of the medication is Appco Pharma LLC, based in Piscataway, NJ, and it is distributed by Cipla USA, Inc. located in Warren, NJ. The medication was batched and released in April 2020 with a GTIN barcode for tracking purposes.*
This text provides information about a medication that should be stored at 25°C, with a temperature range of 15-30°C permitted. The tablets contain sildenafil citrate, with a dosage of 50 mg each. The medication should be dispensed in child-resistant containers. It is manufactured by Appco Pharma and distributed by Cipla USA, Inc. Additional dosage and usage information can be found in the accompanying prescribing information.*
* 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.