Product Images Viracept

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 5 images provide visual information about the product associated with Viracept NDC 53808-0809 by State Of Florida Doh Central Pharmacy, 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.

Label Image for 625 mg - Viracept 625mg (Agouron)

Label Image for 625 mg - Viracept 625mg (Agouron)

VIRACEPT is a prescription medication available in the form of 625mg tablets. The package contains 30 tablets manufactured by Agouron. The lot number for Agouron is 0734069 and the lot number for DOH is 111320083. The medication expires on 053110 and has been packaged by DOH Central Pharmacy in Tallahassee, FL 32304. The code IR WO and the string 6301C027703 are also present but their meaning is unclear.*

Chemical Structure - viracept 01

Chemical Structure - viracept 01

Figure 1 - viracept 02

Figure 1 - viracept 02

This is a figure showing the results of a study (Study S11) on the percentage of patients with HIV RNA below 400 copies/mL. The study compares three different treatments: VIRACEPT 750 mg + ZDVTC (n=39), VIRACEPT 500 mg + ZDVITC (n=97), and placebo + ZDVISTC (n=101). The x-axis shows the study week and the y-axis shows the percentage of patients with HIV RNA below 400 copies/mL.*

Figure 2 - viracept 03

Figure 2 - viracept 03

The text is describing a figure labeled "Figure 2" and showing the mean change from baseline in CD cell counts for a study labeled "S11". The figure compares the mean change in CD cell count for different treatments, including VIRACEPT 750mg + ZDV/ATC, VIRACEPT 500mg + ZDV/TC, and placebo + ZDVI/ATC. The study week is also indicated. However, without the context of the actual figure, it is difficult to provide further details or insights.*

Figure 3 - viracept 04

Figure 3 - viracept 04

* 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.