FDA encourages industry to adopt modeling tools to ensure stable processes

Regulatory NewsRegulatory News | 25 October 2021 |  By 

An official with the US Food and Drug Administration (FDA) encouraged the pharmaceutical industry to adopt advanced process control (APC) modeling tools to ensure that manufacturing processes are operating in a state of control, asserting that these processes are often reactively monitored rather than proactively controlled.
“Our process capabilities remain at two or three sigma, because we are relying on manufacturing of the last century,” said Stelios Tsinontides, director of the FDA’s Office of Pharmaceutical Manufacturing Assessment, speaking in an on-demand session from AAPS PharmSci 360. “I believe we have the tools and the capabilities to bring this level up to a six sigma level,” added Tsinontides, referring to the set of manufacturing process improvement tools pioneered in the 1980s and designed to yield defect-free products through reducing variability. The Philadelphia-based hybrid meeting was sponsored by the American Association of Pharmaceutical Scientists (AAPS).
Tsinontides was describing how process analytical technologies (PAT) tools and multivariate statistical process control (MSPC) can be integrated to ensure that processes remain in a state of control and how these models can be implemented.
FDA officials have long asserted that bringing manufacturing processes up to a six sigma level — a level of performance with just 3.4 defects per million opportunities — can reduce product defects, lower recalls, and produce higher quality products, as well as reduce the risk of drug shortages.
PAT was ‘foundational” in advancing APC
Tsinontides said FDA’s release of its process analytical technology (PAT) guidance issued in 2004 was “foundational” in advancing APC. PAT set out a framework for innovative pharmaceutical development, manufacturing and quality assurance. The framework promotes a system that analyzes and controls the manufacturing process through timely measurements during processing, and incorporates the use of multivariate tools to evaluate process performance. Yet these tools have not been widely adopted in industry.
“PAT and [quality by design] initiatives have contributed to substantial progress; however, I hope that you will agree with me that as industry we have not reached the intended vison that we set in the early 2000s,” said Tsinontides  “We are still focused on monitoring rather than controlling the processes to ensure product quality.”
Tsinontides noted, however, that MSPC “has gained considerable attention in pharmaceutical manufacturing because of its critical role in advancing manufacturing controls in the PAT framework.”
Use of these models is “often linked” to real-time release testing in continuous manufacturing because in this mode of manufacturing, processes cannot be stopped and batches evaluated after each unit of operation, as is the case in conventional batch manufacturing, added Tsinontides.
ICH guideline describes how model can be implemented
Tsinontides said that the International Council for Harmonisation (ICH) Quality Implementation Working Group developed a “points to consider“ document in 2011 to help industry implement MSPC models. The document specifies that the level of documentation in a regulatory submission to support the model depends on its risk.
Models may be categorized as low-, medium- or high-impact, depending on the extent to which they are indicators of product quality.
Models used alongside a “traditional” method for release testing are classified as medium-impact, since they are “useful in assuring quality of the product but are not the sole indicators of process quality,” according to the ICH document. A high-impact model is one that is used as a surrogate for traditional release testing to support a product’s real-time release, requiring more documentation. A model that plays an active role in approving or rejecting a material is classified as either a high- or medium- impact model.
“Our experience with process modeling is growing; we have a dedicated modeling team” within FDA’s emerging technologies team, said Tsinontides. The team is ready to use the “deep knowledge” of its subject matter experts to partner with industry to further develop and adopt the modeling tools, he added.
AAPS PharmSci meeting



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Tags: APC, FDA, PAT, six-sigma

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