Product Images Phytonadione
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Product Label Images
The following 5 images provide visual information about the product associated with Phytonadione NDC 69097-709 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.
Phytonadione is an injectable emulsion, used as a prescription drug, containing 1mg/0.5mL strength in a single-dose vial of 0.5mL. The product contains no more than 500 megL of aluminum and must be protected from light. The code number is HP/DRUGS/L/19/2312/MB and the manufacturer of the product is Cipla Ltd. from India. No additional information is available as the text is cut at the bottom.*
This is a description of a medication called Phytonadione, which is an injectable emulsion, USP. It comes in a 1 mL single-dose vial containing 10 mg/s. The manufacturer is Cipla, with manufacturing and distribution centers in India and the USA. The medication contains no more than 500 mogL of aluminum and should be protected from light during storage. The rest of the text contains various identifying codes and lot numbers.*
This appears to be the packaging of a medicine called "Phytonadione Injectable Emulsion, USP" with a serial number, expiration date, and lot number. It may come in commercial packaging with a separate product called "ISP Seeera Injectable Emulsion" with a different serial number. The rest of the text is unclear.*
This is a product description of Phytonadione Injectable Emulsion, USP with a dosage of 10 mg/mL. The product comes in a single-dose vial and can be administered via intramuscular, subcutaneous or intravenous injection with caution. It is used for commercial packing and overprinting to include product GTIN, serial number, expiry, and lot information. There is also a product code, NOC o047708.36 Rxonly, mentioned in the text.*
* 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.