Product Images Gaboxetine

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Product Label Images

The following 4 images provide visual information about the product associated with Gaboxetine NDC 68405-014 by Physician Therapeutics 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.

Fluoxetine Hydrochloride Structural Formula - FluoxetineHydrochlorideStructuralFormula

Fluoxetine Hydrochloride Structural Formula - FluoxetineHydrochlorideStructuralFormula

FluoxetineLabel - FluoxetineLabel

FluoxetineLabel - FluoxetineLabel

This is a description of a Fluoxetine 10mg capsule with lot number FLT1OVV, manufactured by PLIVA. It has an NDC of 50111-0647-03 and can be compared to Prozac. Instructions to take the medication as directed by a doctor or to refer to the outsert for dosage information are also provided.*

GabaDone - GabaDone

GabaDone - GabaDone

This is a dietary supplement called Z0-¥00T-50F82 in the form of capsules created for adults to manage sleep disorders. The serving size is one or two capsules per day, taken at bedtime or as directed by a physician. The ingredients include proprietary blends of amino acids, herbs, and certain plant extracts, such as cocoa and grape seeds, which help improve sleep quality. This product has no added sugar, wheat, yeast, or preservatives, and should be stored in a dry place at a temperature between 8-32°C. However, this product must be administered under physician supervision and kept away from children. NDC# 68405-1004-02.*

Gaboxetine - Gaboxetine

Gaboxetine - Gaboxetine

This is a medical food and drug that is a convenient package and includes Gaboxetine, "GABAdone" in 60 capsule size, and fluoxetine in 10mg and 30 capsule size. It is only available through a prescription with NDC# 68405-014-26 and requires authorization from a physician to be used as a co-pack.*

* 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.