Product Images Eliquis
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 7 images provide visual information about the product associated with Eliquis NDC 63629-7747 by Bryant Ranch Prepack, 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 appears to be a table of clinical trial data regarding the use of Apixaban versus Warfarin in patients with various subgroups and medical conditions. The table includes information on the number of events and patients, as well as a hazard ratio with confidence intervals for each subgroup. It also includes information on demographics, medical history, and other factors that may impact treatment outcomes.*
The text is a table displaying the Interaction of Drug PK Fold Change and 90% CI for different inhibitors and inducers of P-gp and Strong CYP3A4. The table includes information on the AUC and a calculated Change Relative to Reference. It is not possible to determine the context or purpose of this information without additional information.*
This appears to be a table with recommendations for dosing adjustments based on different conditions such as renal or hepatic impairments, age, body weight, and other factors. The table provides fold change and 90% confidence interval recommendations for each condition. However, there are not enough details or information to determine what medication or drug these recommendations apply to.*
The text should read "This is a medication description for Eliquis 5mg tablets manufactured by Bristol-Myers Squibb Company. The tablets are pink, oval-shaped and identified with 8945. It is stored at room temperature of 20°-25°C (68°-77°F) and should be kept away from children. The tablets come in a package of 60 and expire at a certain date indicated in the format of MM/YY. Its National Drug Code (NDC) is 6362977471 07747601523487."*
* 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.