Study the structure and content trend over time of the FDA GMP Warning Letters for their roles in effective communication.

The structure and content trend over time of Warning Letters are studied using a combination of parsing text based on function, manual coloring and Python automation.

The observed trends using these methods indicate that the content of suggestions on how to respond to a Warning Letter, for third party participation and further reading consistently increases over time.

Warning Letters have become increasingly informative, showing FDA’s good practice of transparency as a way to improve regulatory effectiveness.