Product Images Irbesartan

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Product Label Images

The following 4 images provide visual information about the product associated with Irbesartan NDC 63187-757 by Proficient Rx Lp, 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.

Irbesartan Chemical Structure - eff37327 ff5c 4b80 9ffe 3ab00635bd3f 01

Irbesartan Chemical Structure - eff37327 ff5c 4b80 9ffe 3ab00635bd3f 01

Figure 1-2 - eff37327 ff5c 4b80 9ffe 3ab00635bd3f 02

Figure 1-2 - eff37327 ff5c 4b80 9ffe 3ab00635bd3f 02

Figure 3 - eff37327 ff5c 4b80 9ffe 3ab00635bd3f 03

Figure 3 - eff37327 ff5c 4b80 9ffe 3ab00635bd3f 03

This appears to be a table showing results of a medical study comparing the effectiveness of two different medications (besartan and amlodpine) against a placebo. The table shows the percentage of "Gumuative Event Rats" (presumably meaning the occurrence of negative medical events) over a span of time (21, 24, 27, 30, 36, 39, 42, 45, 48, 51, and 54 months). The results are displayed in two rows ("Frbesartanvs. Placsbo" and "Ibesartanvs. Amiodpine") and show that besartan was more effective than the placebo, but less effective than amlodpine. The text also includes reference numbers for each result.*

63187-757-30 - eff37327 ff5c 4b80 9ffe 3ab00635bd3f 05

63187-757-30 - eff37327 ff5c 4b80 9ffe 3ab00635bd3f 05

This is a bottle of Irbesartan 150mg tablets, containing 30 tablets, with a National Drug Code (NDC) of 63187-757-30. The tablets are white or off-white, capsule-shaped, biconvex and stamped with ‘HH’ on one side and ‘330’ on the other. The manufacturer of this medication is Zhejiang Huahai Pharmaceutical Co., Ltd. and it was relabeled by Proficient Rx LP in Thousand Oaks, CA. The lot number is 00000 and expiration date is 00/00/00. This prescription drug is available only on prescription and should be kept out of reach of children.*

* 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.