PAT and QbD
The FDA’s Process Analytic Technology (PAT) initiative, promulgated in 2004, had the immediate effect of opening up the panoply of chemical analysis tools to bioprocessors. Vendors operating in traditional spectroscopy markets—near-infrared, Raman, and UV/visible spectroscopy—were breaking into biopharmaceutical markets, as medical device companies had done a decade earlier.
A scan of the literature shows how radically new sensing modalities depart from traditional quantitation of pH and glutamate. PAT also inspired development of novel sensor and monitoring technologies for “old” parameters, particularly for instrumentation and data handling.
From the perspective of operations, PAT’s major industry-wide success has been bringing process monitoring closer to the process. FDA defines analytics as being offline (far away), at-line (in the same room), and inline, which roughly correspond to cycle times of days/hours, hours/minutes, or more-or-less real time.
Bioprocessors now have a better appreciation for shorter analysis times and greater proximity to where the action is. Bioprocess monitors that measure routine parameters (pH, DO, etc.) are most often deployed in-line, but other technologies are moving toward the bioreactor at a snail’s pace. One often-cited reason is that production suites were designed for manufacturing, not analytics, and that space can be tight.
Regardless, eight years after PAT, analyzers have become more sophisticated and robust, while biomanufacturers have a much more refined sense of monitoring, quality, and risk minimization. This is due in no small part to FDA’s well-reasoned connection of PAT, process understanding, and quality by design (QbD). These three factors have come to form the predominant business case for advanced process monitoring and control.
Their connectedness look great on paper, and sound great in theory. Building a strong business case for higher quality, products that are safer and more effective, and fewer batch failures is easy. Nevertheless, the uptake of advanced sensing and monitoring schemes has been painfully slow.
PAT’s promise to deliver “process understanding” and enable QbD is based on the premise that analytics will provide an actionable (or predictive) understanding of critical process parameters affecting quality, which will lead to higher-quality product and/or less waste.