Product Images Vasopressin
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Product Label Images
The following 8 images provide visual information about the product associated with Vasopressin NDC 51662-1314 by Hf Acquisition Co Llc, Dba Healthfirst, 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.
VASOSTRICT™ (VASOPRESSIN INJECTION, USP) is a medication that comes in 2 units per mL in a vial. It is only for intravenous infusion and requires dilution before use. The product has to be stored between 2°C and 8°C, but it can be held at 20°C to 25°C for up to 12 months. The prepared infusion solution should be discarded after 18 hours at room temperature or 24 hours refrigerated. VASOSTRICT™ is manufactured by HFAcquisitionCo., LLC for Rx only. Full prescribing information should be reviewed. The original manufacturer's NDC code is 42023-164-25, and this product's NDC is 51662-1314-2. Lot 123456 with an expiration date of 2025-81-81.*
This is a set of storage instructions for a refrigerated product that should be kept at a temperature range of 2°C to 8°C (36°F to 46°F) if unopened. If unopened and stored at room temperature, it should be kept in the range of 20°C to 25°C (68°F to 77°F) but not stored above 25°C (77°F). The expiration date for an unopened container is dependent on the manufacturer's date or 12 months. Once opened, the product should be used within 30 days or per the manufacturer's instructions.*
This is a pharmaceutical product that is distributed by HF Acquisition Co., LLC in Mukilteo, WA. It can only be used with a prescription from a licensed healthcare professional. The text includes some identification numbers and a reference to the manufacturer's package insert, which likely contains important information about the product, including its uses, dosage information, potential side effects, and other important details.*
* 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.