In Peter Baker’s first presentation with Redica Systems on quality intelligence, he spells out how he sees pharma companies actually reaching the goal of modern quality intelligence, based on FDA guidance, 483s, and other sources—a long road trip with several stops and no shortcuts.
The former FDA investigator and current President of Live Oak Quality Assurance also shares what he thinks firms will need along the way and what they might discover when they get there.
“Everybody’s aiming for this world-class manufacturing,” says Baker in his presentation, “Quality Intelligence: from Data to Intelligence.” But there’s a barrier holding the industry back, keeping firms on a “hamster wheel of deviations and CAPAs, deviations, and CAPAs.”
That barrier is lack of knowledge, he says. And busting through means being able to take data—paper and electronic—put it in context to generate information, organize it systematically into knowledge, then figure out how to use that knowledge to get off the hamster wheel.
That’s the road to quality intelligence. Baker’s roadmap—which we’ll summarize here but is best explained by the man himself—shows the “stops” he expects firms to need to take. They’ll also need to pick up certain “provisions” to make it to later stops in the trip.
For example, management review (established in Stop 3, below) can’t handle 100 issues a month. How can a risk-based review framework ensure that management review is aligned with current regulatory expectations? They’ll need data tools alongside employee empowerment, which firms pick up at Stop 1.
“It’s a long drive, folks,” says Baker. “Don’t forget the essentials. Don’t forget the water. Don’t forget your snacks … we can’t skip any of the steps along the way, right? There aren’t really shortcuts allowed—that [would] cause us to trip up, and in fact, have to go backwards.”
- Stop 1: Data Integrity
- Key practice: Promoting and using ALCOA+ principles
- Provisions for the road: Employee training and empowerment
- “Many of us already started—for example, [with] the initial MHRA guidance document on data integrity—all the way back in 2015,” he says. “We already have ALCOA+ principles ingrained in our quality systems through training, through the way we write documents, through the way we set up software control programs.”
- Stop 2: Data Governance
- Key practice: Adopting a risk-based approach
- Provisions for the road: Quality risk management tools, including mapping and qualitative risk assessment
- First appearing in the 2019 PIC/S guidance document on data integrity, Baker says data governance allows firms to acknowledge that data integrity is never going to be perfect, so they can adopt a risk-based approach.
- Stop 3: Quality Culture/Mindset
- Key practice: Establishing a quality system consistent with ICH Q10
- Provisions for the road: Management review
- “It makes this connection to not only what you do—yeah, it’s in the SOP—but why you do it,” says Baker.
- Stop 4: Knowledge Management
- Key practice: Adopting FAIR Principles, an optimization framework
- Provisions for the road: Agile-ish validation, such as in the FDA “Computer Software Assurance” guidance
- “FAIR” as in Findability, Accessibility, Interoperability, and Reuse of digital assets—Baker recommends this presentation by QbDVision CEO Yashvinder Sabharwal. Knowledge management is a “systematic way of organizing data and metadata that we already collect in our pharmaceutical quality system [in order] to use that data in different ways,” he says. Middleware and data lakes are the types of solutions implementing the ICH Q10 concept of knowledge management.
- Stop 5: Visualization
- Key practices: Dashboarding, vigilant operations management oversight
- Provisions for the road: Critical thinking
- Dashboards are essential for visualizing data within a pharmaceutical quality system, while “vigilant operations management” is straight out of recent FDA warning letters, which Baker takes to mean focusing on data to “vigilantly monitor your process in order to determine the current state of your quality system.”
- Stop 6: Quality Intelligence
- Key practices: Glimpses in FDA discussion paper “Artificial Intelligence in Drug Manufacturing.”
- “This is that maturity step that we’re all really aiming for,” says Baker. “FDA has an entire whitepaper dedicated to quality management maturity, right? This is one of the aspects that is going to allow you to demonstrate maturity to the regulators, and take advantage of what they’re offering within that white paper.”
What Will the Industry Find When It Arrives?
“We filled up that gas four or five times along the road, and we’re finally there, which is quality intelligence,” says Baker.
But what might quality intelligence allow FDA-regulated life sciences firms to do once they master it? Baker’s main bet is on “relationality,” the concept that there are deep interconnections among people or things, such as the components of a drug manufacturing process.
“Say you have a pH value that’s an in-process control, maybe step four or five along an eight-step process. So that represents data, right?” says Baker. “Could that pH value—regarding how high or low it is within our specification limits—could that predict how future steps along the process are going to perform?”
“That is the relationality,” he says, “And this is really the goal of intelligence, really like advancing our understanding of our process.”
Keep Reading the Road Signs
Sketching out his roadmap, Baker interprets where the FDA is trying to lead the industry based on the agency’s focus in regulation, discussion papers, and many other sources.
But the FDA is always refining its approach, and it’s not always possible for everyone in the industry to keep up. Plenty of useful guidelines and hints are sprinkled throughout the agency’s publications, sometimes where you might not expect them.
Connecting the Dots with Redica Systems
Redica Systems helps your teams connect the dots, and the relevant regulatory surveillance signals get delivered to your inbox. So you can keep up with the FDA road signs that are most important to your company’s journey to quality intelligence. And you’ll take advantage of the most comprehensive and digestible feed of regulations and standards, built by our team of experts using advanced machine learning models.
Contact Redica Systems for a walk-through today!
Subscribe to Redica Insights
Get quality and compliance insights from our experts in your inbox