Doxazosin Tablet
Product Images NDC 42291-259

View Photos of Packaging, Regulatory Labels, and Product Appearance

Product Visual Gallery

This gallery contains 6 technical images submitted to the FDA as part of the official labeling for Doxazosin (NDC 42291-259). Unlike standard consumer photos, these assets often include clinical data figures, molecular chemical structures, and official manufacturer packaging layouts.

As provided by Avkare, these visuals offer a comprehensive scientific overview of the product's physical and chemical identity, aiding pharmacists and researchers in product verification and study.

Product Images & Figures Index

FDA Label Image

Label 2mg 2015 04 09 At 10.41.29 Am

Label 2mg 2015 04 09 At 10.41.29 Am
AVKARE is a pharmaceutical company that produces Doxazosin Tablets, USP which come in a pack of 1000 tablets with the imprint R on them. The National Drug Code for this medication is 42291-258-10.*
FDA Label Image

Label 4mg 2015 04 09 At 10.42.43 Am

Label 4mg 2015 04 09 At 10.42.43 Am
FDA Label Image

Label 8mg 2015 04 09 At 10.43.48 Am

Label 8mg 2015 04 09 At 10.43.48 Am
FDA Label Image

Doxazosin-structure (Doxazosin Structure)

Doxazosin-structure (Doxazosin Structure)
FDA Label Image

Figure1

Figure1
FDA Label Image

Table3

Table3
This is a summary of effectiveness data from placebo-controlled trials for the treatment of Benign Prostatic Hyperplasia (BPH). The data includes changes in the maximum flow rate (mL/sec) and symptom score. The results show that doxazosin at both 4mg and 8mg doses improved these measures when compared to placebo. Additionally, the Modified Boyarsky Questionnaire was administered in Study 2. Change was measured at endpoint and at fixed-dose efficacy phase, 2-6 hours post-dose depending on the study. Study 1 is focused on hypertensives with BPH and 35 patients received an 8mg dose of doxazosin. Statistically significant improvements were observed with both doses of doxazosin compared to placebo.*

* These product label images have been analyzed using experimental machine learning. Please verify findings with the primary label text.