Product Images Enpresse

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 6 images provide visual information about the product associated with Enpresse NDC 54868-4860 by Physicians Total Care, 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.

image of package label - 4860

image of package label - 4860

This is a packaging label for Enpresse 28 tablets, distributed by Physicians Total Care. The label includes details such as the National Drug Code (NDC) and lot number with an expiration date. The manufacturer listed is WO W e LascmaToRIES, D. There is also a barcode included with the text "48600730000".*

Structural Formula - 49881bd9 2c69 430c a563 c9834a064718 01

Structural Formula - 49881bd9 2c69 430c a563 c9834a064718 01

Structural Formula 2 - 49881bd9 2c69 430c a563 c9834a064718 02

Structural Formula 2 - 49881bd9 2c69 430c a563 c9834a064718 02

Figure 1 - 49881bd9 2c69 430c a563 c9834a064718 03

Figure 1 - 49881bd9 2c69 430c a563 c9834a064718 03

Figure 2 - 49881bd9 2c69 430c a563 c9834a064718 04

Figure 2 - 49881bd9 2c69 430c a563 c9834a064718 04

This is a birth control pack called "Enpresse" with 28 pills. It contains white and orange-colored tablets and light-green tablets. The white and orange pills contain levonorgestrel and estrogen and need to be taken on days labeled with "SN", "MON", "TE", "we)", "THU", "P", and "saT|fep". The light-green tablets are reminder pills and can be taken on any day.*

Figure 3 - 49881bd9 2c69 430c a563 c9834a064718 05

Figure 3 - 49881bd9 2c69 430c a563 c9834a064718 05

The text is a simple set of instructions for labelling specific days of the week. It provides an example of the format for the labels and specifies which days of the week should be included. It is not available whether this refers to a particular product or use case.*

* 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.