Artificial Assistance
As I was addressing audience comments submitted following my recent webinar on Quality Intelligence, the question was posed: “can you comment on the importance of Artificial Intelligence and Data Analytics in drug manufacturing?” During my response, I stated that “advanced data analytics will allow our industry to improve process control strategies in ways we cannot comprehend without artificial assistance”. Artificial Assistance? Surely someone has termed that phrase, so I Googled it, but alas – Google did not provide me with a definition, but rather directed me to links advertising various artificial assistants (totally different thing, but very cool!). I was hoping to reference another trendy term in this new world where AI and the pharmaceutical industry convergence, but no such luck.
The reason I felt compelled to Google the phrase was that as the two words appeared on my screen, I immediately felt that it described the “intended use” (see 21 CFR Part 11.10(a)) of the various AI tools within our heavily regulated industry. When we define the intended use, we can then proceed with a validation strategy. We can feel confident moving forward alongside AI solutions, addressing the validation hurdle by considering how these tools are to be used: artificial assistance. One example that comes to mind: AI will enhance (or “assist”) the human (QA) to ensure that the final batch disposition decision is based on our best efforts of analyzing the data set for any indication of a quality defect. In this context, the validation burden becomes manageable using existing qualitative risk-management tools outlined in ICH Q9, considering the “intended use”. Risk to patient safety introduced from use of these tools can be managed by demonstrating that the decision (disposition) will not be based solely on the outcome of an AI algorithm alone, without human verification, but rather an enhancement of traditional human data review and approval processes alongside an artificial assistant that improves the disposition process in a demonstrable manner.
Two is always better than one!
It would be foolish to move ahead with the attitude that AI will not introduce risk to the example mentioned above, but why would we let risk prevent us from improving the process? No great innovations come about without confronting new challenges. By acknowledging and managing risk, humans have been improving processes since the beginning of time! All innovations present new and different hazards, but lucky for us a clear and concise roadmap for risk management has already been provided by the regulators!
We already have the tools - so let’s get started!
Pete
