AI in Drug label management - Datafoundry
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Oct 18th, 2021
AI in Drug Label Management

Label Management

Label Management is a process which helps in complying with regulatory requirements and FDA guidelines. Labeling protocols are a set of specific requirements for the labeling of the final product. These protocols are set by regulatory authorities and they include national, regional, or international sets of standards.

Labeling protocols help to provide information about how a product should be labelled in order to comply with safety, regulatory, and other legal requirements. It is important that these protocols are followed correctly because there may be penalties for not following them.

Label Data Management

Labels are used to classify and identify the contents of containers, packages, and objects by product type, function, features, or content. Labeling data management (LDM) is the process of managing labeling data in order to make it available for use in enterprise operations.

Labeling data sheets are mainly documents that provide information about the physical characteristics of a container or package for labelling purposes. They contain all necessary information like parts parts identification (PID), part number (PN), type of container (TC), chemical name or synonym (CN), classification code (CC), can size code (CS) and more.

Labeling lab is the place where labels are created through cutting machines and other equipment by applying different printing techniques like screen printing, flexography and many more.

Label Changes and How AI can Manage Them

Labels are necessary to make sure that products are safe and can be consumed. AI is becoming more and more important in labeling changes because it can correct the labeling process and protocol.

Correct labeling protocol is essential for food or drug safety. Manufacturers need to ensure that they comply with the correct labeling process before they ship any product.1 One of the most popular ways of achieving this is by using AI-powered label management systems to help manage label changes.

Why Are Drug Labels Difficult To Manage?

Drug labels are difficult to manage for a number of reasons. One, they are often published in a language that the consumer does not understand.2 This calls for translation from the original language to English, which is time-consuming and costly. Two, there is an international standard for drug labeling that requires drugs be labeled in both the marketer’s own language and the language of the country where it is marketed.

This makes it so that drug labels have to be produced in at least two languages! Three, many drug labels contain all sorts of terminology and symbols which can lead to confusion among patients who read them regularly.

Thus, over time, drug labeling has become more difficult than it needs to be because of these factors combined with people not being educated about how to use medication properly.

Drug Label Approvals and How to Secure Them

Drug labels are important because they provide information about an approved drug. They specify the ingredients, dosage, usage instructions, warnings and potential side effects of the drug. But what is often overlooked is that they also must adhere to FDA guidelines in order to be approved.

The FDA regulates the safety and effectiveness of food, drugs, vaccines, medical devices, cosmetics, dietary supplements, and more.

The FDA’s ultimate responsibility is to ensure that the information on drug labels is accurate.

Conclusion & Next Steps : Wrapping Up the Drug Label Management Process

The drug label management process can be a time-consuming and difficult task for labelers to complete. With the help of a labeler, it’s easier to manage this process.

The FDA requires that all prescription drugs have a label on them detailing their ingredients, risks, side effects, and dosage. In the event that someone takes too much of the drug or has an allergic reaction, they can refer back to this information for quick relief from any issue. This process needs to be done in order for drugs to enter the market and be sold legally.

Role Of Datafoundry In Automating Label Management

DF mLabel AI is an AI-driven label management solution that helps companies organize, deliver, and track product information. It is a simple solution for label management and review which automates the entire Label review and QC process; from receiving and ingesting artwork to generating Digital Labels for drug trials and post-marketing. Our NLP division is on the forefront of data digitization, and we’re inventing new ways to tackle your most complex labelling challenges.

Talk to our experts to know how we can solve your label management problems.


  1. (accessed October 1, 2021).
  3. (accessed October 1, 2021).

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