Product Images Paroxetine
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Product Label Images
The following 8 images provide visual information about the product associated with Paroxetine NDC 13107-156 by Aurolife Pharma Llc, 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.
Each film-coated tablet contains 10mg of paroxetine hydrochloride USP. The tablets are distributed by Aurobindo Pharma USA, Inc. and usual dosage information can be found in the accompanying prescribing information. They should be stored in a tight, light-resistant container at 20°C to 25°C (68°F to 77°F); excursions are permitted within 15°C to 30°C (59°F to 86°F). The medication guide is provided separately and safety closures should be used during dispensing, unless otherwise noted. The NDe number is 13107-154-30 and the lot number is 0472017.*
Each tablet of this medication contains 30mg of paroxetine hydrochloride, distributed by Aurobindo Pharma USA Inc. See the prescribing information for usual dosage. Store between 20-25°C (68-77°F) with excursions allowed up to 15-30°C (59-86°F). Dispense in a light-resistant container with safety closures. A medication guide is provided separately. NDC 13107-156-30.*
Paroxetine Tablets, USP are for prescription use only. This medication is dispensed with a medication guide that is provided separately. Each package contains 30 film-coated tablets of paroxetine hydrochloride USP, equivalent to 40 mg of paroxetine. The usual dosage is described in the accompanying prescribing information. Store this medication at a controlled room temperature of 20-25°C (68-77°F), with excursions permitted to 15-30°C (59-86°F). Dispense in a tight, light-resistant container and use safety closures unless directed otherwise by the physician or requested by the purchaser. Distributed by Aurobindo Pharma USA, Inc. This product was last revised in April 2017.*
* 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.