Product Images Aripiprazole
View Photos of Packaging, Labels & Appearance
Product Label Images
The following 11 images provide visual information about the product associated with Aripiprazole NDC 71335-1893 by Bryant Ranch Prepack, 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.
Figure1 - Figure1

This is a list of drugs that may affect the metabolism of Aripiprazole, a medication used to treat mental/mood disorders including bipolar disorder and schizophrenia. The list includes inhibitors and inducers of various enzymes that are involved in the metabolism of Aripiprazole, such as CYP2D6 and CYP3A4. The text provides information on the fold change and 90% confidence interval for Aripiprazole in the presence of these drugs.*
Figure2 - Figure2

This text provides information on the effect of certain drugs on the drug aripiprazole. It categorizes the drugs based on their inhibiting or inducing effects on certain enzymes. The text also presents a chart showing the fold change and CI of dehydro-aripiprazole with various drugs. There is a mention of drugs like ketoconazole, quinidine, carbamazepine, famotidine, valproate, and lorazepam.*
Figure4 - Figure4

The text describes different populations and their pharmacokinetics (PK) in relation to taking Avripiprazole. It mentions the effects of CYP206 metabolism, gender, age, hepatic impairment, and renal impairment in terms of AUC and maximum concentration (max) levels. It also shows fold change and percentage change relative to a reference.*
Figure5 - Figure5

This appears to be a table showing the effects of various factors on the metabolism of a drug, possibly Aripiprazole. The factors include genetic differences in CYP2D6 enzyme activity (poor vs. extensive metabolizer), gender (male vs. female), age (16-64 vs. over 65 years old), and hepatic impairment (mild, moderate, or severe compared to normal). The effects are measured by changes in area under the curve (AUC) and maximum concentration (max) of the drug, as well as fold change and 90% confidence intervals of the breakdown product Dehydro-Aripiprazole. The effects of renal impairment on AUC are also shown, but the text is cut off, making it difficult to interpret the severity of the impairment.*
Figure 6 - figure 6

This appears to be a chart comparing the effectiveness of Aripiprazole and Placebo in preventing relapse. The chart shows the proportion of subjects who experienced relapse over time (in days from randomization) and the number of subjects at risk for each drug. The chart shows that Aripiprazole has a lower proportion of relapse compared to Placebo over time.*
Figure 7 - figure 7

This appears to be a graph or chart with numbers and labels indicating the proportion of relapse with a specific medication compared to a placebo over a certain period of time. The medication being studied is "Avripiprazole". There is also a list of numbers indicating the "number of subjects at risk" for the study. However, without more context or a clearer image, it is difficult to provide a more detailed description or analysis.*
Figure 8 - figure 8

This text appears to be a chart or graph displaying the results of a study involving the drug Aripiprazole and a placebo, with data being shown over time. The chart includes a "proportion with relapse" and a "number of subjects at risk" for both Aripiprazole and the placebo. However, the specifics of the study, such as what condition or illness is being treated, are not available.*
Label - lbl713351893

This appears to be a package label for a 5mg tablet of Abilify produced by Hetero Labs Limited. The package was pre-packaged by Bryant Ranck and comes in a quantity of 30 tablets per package. The National Drug Code (NDC) for this package is 7133518931. The package should be stored at room temperature (20°-25°C or 68°-77°F) and kept out of the 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.