Product Images Alprazolam
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 9 images provide visual information about the product associated with Alprazolam NDC 67296-1748 by Redpharm Drug, 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.
This is the description of a medicine called Alprazolam 0.25mg. It comes in the form of 10 tablets and is only available through a prescription. The usual adult dosage is mentioned in the package insert. The medicine is manufactured by Centaur Pharmaceuticals Pvt. Ltd. in Maharashtra, India, and distributed by Redpharm Drug in Eden Prairie, MN, USA. The medicine should be stored at controlled room temperature between 20-25°C (68-77°F). The lot number is 190840X1, and the expiration date is 04/21.*
This text contains information about a medication package with a GTIN of 0351991704010, SN of XXOXXKKOXXK, and an expiration date of MM/YYYY. It also includes a lot number of 1234567 and the NDC code 5199170401 for Alprazolam tablets, USP. The instructions for use are not readable and thus are not available.*
This is a description of a medicine with the brand name MHDRUGSPDITE2 manufactured by TGS CEVTAOR PARMACEUTIELS PV (T). The packaging contains tablets of Alprazolam with a strength of 0.5 mg. The batch number, expiry date, and the GTIN code of the product are available on the package. The text includes dosage information, and the brand claims to provide relief from anxiety disorders.*
This is a product label containing information such as GTIN (the product identification code), SN (Serial Number), EXP (Expiration Date), a LOT number, and dosage instructions for Alprazolam tablets. The label also mentions the manufacturer's name and the name of the pharmaceutical company distributing the product.*
* 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.