Here is the paper, this post is for educational purposes only. I am not employed by or speak for the FDA. I am just a Document Control professional who works in a space governed by FDA policies & procedures. This is also not a reflection of the thoughts and options of my employers. The points made in this post are entirely my own.

Hi Hey Hello,

On March 3rd, 2023, the FDA published a discussion paper proactively preparing the public for the implementation of AI (Artificial Intelligence) in drug manufacturing.

The paper starts by recognizing the power and potential that AI has in drug development. The FDA specifically stated that AI in reference to cGMP is out of the scope of this discussion paper. Could any of these AI applications support your organization?

The Highlights:

1. Process Design: AI could be leveraged to streamline/speed up the process of identifying optimal processing conditions and decrease development time/wasted resourcing.
2. Trend Monitoring: I love a metric, the FDA sees AI as a tool to be used to process consumer complaints and quality events (Deviations). It can create visual graphics of the data that could help researchers to identify problems and prioritize areas of improvement.
3. Monitoring Equipment/Process: AI can be leveraged to monitor equipment, predict potential failures and trigger automatic or manual maintenance requests.
4. Third-Party/Suppliers: For data storage specifically, if your supplier uses AI may not have appropriate securities in place for critical, confidential, and/or private data. Make sure to have additional controls in place (quality agreement) to make sure your data is protected.
5. More Data: Using AI could result in more data points being collected during the manufacturing process. Your team might need to consider ways to balance the influx of data by creating procedures on what data is valuable for storage/retention and how critical data loss at each point in your manufacturing process would impact product quality.
6. AI Validation Modules and Standards: You need to understand the full scope of potential results the AI can provide. Some potential questions to consider: Where is the information being pulled from and how are decisions being made? If you are transitioning to a new AI, how is that information being migrated?

My thoughts and conclusions: AI is a powerful tool. The FDA sees and supports the potential benefits. If you choose to implement AI, plan to have robust quality checks throughout your process.