Product Images Tums Chewy Delights

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 3 images provide visual information about the product associated with Tums Chewy Delights NDC 0135-0569 by Haleon Us Holdings 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.

Tums Chewy Delights Smooth Peppermint 32 count card - cb250cbb 322a 4145 bbeb eaf5aa8122de 01

Tums Chewy Delights Smooth Peppermint 32 count card - cb250cbb 322a 4145 bbeb eaf5aa8122de 01

This appears to be a product label containing information about a peppermint-flavored soft chew supplement. The product has an NDC number of 0135-0561-01 and is described as having "Ultra Strength" with a smooth peppermint flavor. The soft chews are individually wrapped for convenience.*

Tums Chewy Delights Very Cherry 32 count card - cb250cbb 322a 4145 bbeb eaf5aa8122de 02

Tums Chewy Delights Very Cherry 32 count card - cb250cbb 322a 4145 bbeb eaf5aa8122de 02

This text contains a product code (NOC 0135-0560-01) followed by some scanned graphics that include the words "NOES 70 WORK" and "SOFT CHEWS". The graphics also show that the soft chews are individually wrapped, but no details are provided about the contents, ingredients, or purpose of the product. Therefore, based on this text alone, it is not possible to provide a specific description of the product or its use.*

Tums Chewy Delights Orange Rush 32 card - cb250cbb 322a 4145 bbeb eaf5aa8122de 03

Tums Chewy Delights Orange Rush 32 card - cb250cbb 322a 4145 bbeb eaf5aa8122de 03

This is the description of a medication with the NDC code 0135-0569-01. The brand name of the medication is not clear from the available text. It appears to be a soft chew medication with ultra strength, and the chews are individually wrapped. No other information is available.*

* 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.