Product Images Paclitaxel Protein-bound Particles For Injectable Suspension (albumin-bound)
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 6 images provide visual information about the product associated with Paclitaxel Protein-bound Particles For Injectable Suspension (albumin-bound) NDC 60505-6230 by Apotex Corp., 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.
Slowly inject the 20 mL of 0.9% Sodium Chloride Injection, USP, over a minimum of 1 minute, using the sterile syringe to direct the solution flow onto the INSIDE WALL OF THE VIAL. - pacli 01
Structural Formula for Paclitaxel - pacli 02
Figure 1: Kaplan-Meier Curve of Overall Survival (Intent-to-Treat Population) - pacli 03
PRINCIPAL DISPLAY PANEL - 100 mg Vial - pacli 04
This is a description of a medication product. It is a vial of Paclitaxel Protein-Bound particles for injectable suspension, containing 100 mg per vial. The suspension is albumin-bound, and the NDC (National Drug Code) number is 605056204. The rest of the text appears to be a product code and is not useful for providing a description.*
PRINCIPAL DISPLAY PANEL - 100 mg Vial - pacli 05
This is a medication containing Paclitaxel Protein-Bound in injectable suspension form, with 100mg of medication per vial. The medication appears to be manufactured by Apotex Corp, with a product code of NOC 6050562904 and a batch number of 112450. The remaining text is not readable or in English.*
PRINCIPAL DISPLAY PANEL - 100 mg Vial Carton - pacli 06
This text seems to be a product label or drug information sheet. It includes information on a "Particles for Injectable Suspension" that comes in a vial with 100mg per vial. The rest of the text is not-readable or contains symbols and characters that cannot be recognized.*
* 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.