Product Images Bortezomib
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Product Label Images
The following 8 images provide visual information about the product associated with Bortezomib NDC 0781-3258 by Sandoz 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.
carton - carton

This is a description of Bortezomib for injection, a drug that is administered through subcutaneous or intravenous injection. The contents of the Lyophilized vial contain 35 mg of bortezomib and 35 mg of a substance that is not specified. The usual dose is not mentioned and must be found in the accompanying package. The drug must be stored at 25° C (77° F) with some excursions permitted and protected from light. The text also provides information on how to reconstitute the drug for use. The manufacturer of the drug is Sandoz, and the NDC code is 0781-3258-70.*
Figure 1 - image 02

This appears to be a figure or graph comparing the time to progression for two treatments in patients. One treatment includes bortezomib, melphalan, and prednisone while the other only includes melphalan and prednisone. The percentage of patients is shown on the y-axis and the time in months is shown on the x-axis. However, the text is not clear and includes some non-English characters, so this description may not be entirely accurate.*
Fig 3 - image 04

The text appears to be a figure caption depicting a study on relapsed multiple myeloma. The figure shows a time-to-progression comparison between Bortezomib and Dexamethasone treatment. Unfortunately, the text is incomplete and contains errors. Therefore, the description may not be entirely accurate.*
Figure 5 - image 06

This text does not provide enough context to generate a meaningful description. It appears to be a table or chart with some statistical analysis results, but the information is incomplete and there is no clear indication of what it pertains to.*
* 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.