Product Images Ruby-fill
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 8 images provide visual information about the product associated with Ruby-fill NDC 65174-021 by Jubilant Draximage Inc., Dba Jubilant Radiopharma, 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 text is a label of Ruby-Fill 502125 Rubidium Rb 82 Generator including the lot number, calibration date and activity details. It also has a bar code.*
This seems to be a calibration table showing the relationship between dose calibration readings and Sr 82 and Sr 85/Sr 82 ratio in different units of measurement (meCi and kBq). It also provides correction factors for the readings. This table is likely used in nuclear medicine or radiation therapy.*
This text provides a reference in empirical units (meCi) and international units (kBq) for two radioactive isotopes of strontium (Sr 82) and rubidium (Rb 82). It also includes calculations to convert between these units. The text also includes a note about the alert limits for Sr 82 and the requirement for additional daily eluate testing.*
This is an outer label number 2 designed for identification purposes. The label is related to a Rubidium Rb 82 Generator called RUBY-FILL® with product code 502125.*
This is a description of a medical product used for intravenous diagnosis containing Rubidium Chloride Rb 82. The product comes in a generator column containing Strontium-82 adsorbed on anhydrous stannic oxide. The usual dosage and instructions for use are available on the package insert. The medical product must be stored at 20-25 °C and handled carefully by qualified personnel in accordance with regulations and licensing requirements. It is radioactive material and requires proper radiation safety precautions at all times. The product is manufactured by Jubilant DRAXIMAGE, Inc.*
* 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.