Product Images Simponi Aria

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 4 images provide visual information about the product associated with Simponi Aria NDC 57894-350 by Janssen Biotech, 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.

Figure 1 - simponi 01

Figure 1 - simponi 01

The text represents a graph showing the response rate of patients, in terms of ACR 20, over a period of 24 weeks. Two drugs are compared, Placebo + MTX and SIMPONI ARIA 2 mg/kg + MTX. The X-axis indicates the number of weeks and the Y-axis represents the percentage of patients responding to the treatment. The graph shows that the SIMPONI ARIA 2 mg/kg + MTX drug had a higher percentage of ACR 20 responders compared to the Placebo + MTX drug over the 24-week period.*

Figure 2 - simponi 01a

Figure 2 - simponi 01a

This is a graph showing the percentage of ACR 20 responders over time (in weeks) for four different treatments (placebo, SIMPONI ARIA 2 my/kg). The percentages are represented as points along the y-axis (ranging from 0% to 70%). The x-axis represents time in weeks. There doesn't seem to be any additional information available to provide a more detailed description.*

Figure 3 - simponi 01b

Figure 3 - simponi 01b

This appears to be a graph or chart with the title "SIMPONI ARIA Zm" and the x-axis labeled "time (Weeks)" while the y-axis appears to be labeled "Percent ASAS 20 Responders." The data points on the y-axis range from 0 to 70 with intervals of 20, while the x-axis shows values labeled as "s0", "s", and "2". Without further context, it is unclear what the data represents or what the chart is trying to convey.*

PRINCIPAL DISPLAY PANEL - 4 mL Vial Carton - simponi 02

PRINCIPAL DISPLAY PANEL - 4 mL Vial Carton - simponi 02

* 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.