Validation 4.0 Series
Part 4: What is Validation 4.0?
As part of my involvement with the ISPE Validation 4.0 Working Group, which is part of the ISPE Pharma 4.0 Community of Practice , I am often asked, “What is Validation 4.0?” That’s a very good question! I hope to answer this question through a series of articles.
Part 1 answered the question, “What is Validation?” Part 2 answered the question, “What is Holistic Control Strategy?” This article, Part 3, will answer the question, “What is Pharma 4.0?” Read on to learn more:
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Two Key Questions
Previous articles in this series discussed viewing validation as a demonstration that drug product manufacturing processes are in a state of control, understanding control strategy holistically rather than merely controlling Critical Process Parameters (CPPs), and understanding the technological and other industry changes that comprise Pharma 4.0. It is within this context – new paradigms, new technologies, and new expectations – that we must consider the impact on our understanding of validation, both as a lifecycle process and as an industry.
To that end, and as discussed previously in this ISPE Pharmaceutical Engineering article , the validation industry must ask ourselves two questions:
Let’s begin to answer those questions by taking a look at validation paradigms and methodologies, how they have changed, and how they need to continue to change.
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Prior Evolution of Validation Methodology
Although validation as a formal lifecycle process didn’t exist in the earliest iterations of the pharmaceutical industry – the first Good Manufacturing Practice (GMP) regulations were passed into law in the US in 1963, and it wasn’t until 1979 that two US FDA officials proposed the concept of validation (see here for an excellent read on the history of validation ) – the principles of validation can be traced through the evolution of the industry from Pharma 1.0 through to today.
Pharma 1.0
In the Pharma 1.0 paradigm, manufacturing was a compounding pharmacy cottage industry that primarily produced oral solid and liquid drug products. Any process control was implicit, as was any product and process knowledge.
Pharma 2.0
In the Pharma 2.0 paradigm, products were developed through research and development, incorporating principles of Quality Risk Management (QRM) in which Product Critical Quality Attributes (CQAs) and their associated process Critical Process Parameters (CPPs) were identified. Here, the control paradigm was unidirectional, from product specifications to finished product testing, based on identified CPPs and CQAs. Product and Process Knowledge consisted of direct relationships between CQAs, CPPs, and Critical Material Attributes (CMAs).
Validation in the Pharma 2.0 paradigm consisted mostly of identifying and demonstrating control of CPPs and demonstrating through testing that the process produced drug product meeting its CQAs. This validation paradigm may be best represented by the validation “V-Model”.
Pharma 3.0
In the Pharma 3.0 paradigm, principles of Quality by Design (QbD) were incorporated into the design and development of the drug product manufacturing process lifecycle. CPP-based control of CQAs evolved from a direct relationship to the concept of iterative control within the design space, acknowledging the secondary and tertiary relationships between process parameters and product quality, and also the interactions between multiple CPPs and their associated CQAs.
Validation in the Pharma 3.0 paradigm evolved to incorporate a lifecycle process view of validation, to incorporate the principles of Quality Risk Management (QRM) and Quality by Design (QbD), and Good Engineering Practice (GEP) best practices to facilitate effective, efficient approaches. This validation paradigm includes both the legacy “Commissioning and Qualification (C&Q)” approach and the successor QRM-based C&Q approach defined by ASTM E2500, ISPE Baseline Guide, Volume 5, 2nd Edition, and the ISPE Good Practice Guide: Good Engineering Practice, 2nd Edition.
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Current Manufacturing and Validation Paradigms
In terms of manufacturing technology, innovation has historically been iterative, slow-to-adopt, and implemented from a risk-averse perspective. The manufacturing process has traditionally been batch processing. Batch sizes have ranged from a few hundred doses for boutique drug products to tens of thousands of doses for bulk-manufactured products. The primary technology driver has been process automation. In terms of information technology, data management has traditionally been highly controlled and siloed, with centralized data collection. In terms of process control strategy, process control has been primarily reactive, based on process changes either within fixed CQA/CPP ranges or within the design space.
Current validation methodology tends to be linear through the validation lifecycle. It tends to be prescriptive with respect to process control. And demonstration of the process control strategy still tends to be a point-in-time documentation of the traditional “Three Golden Batches.”
Traditionally, and like the rest of the Pharmaceutical Quality System (PQS) of which it is a part, due to risk aversion and fear of reaction by regulators, validation has largely been viewed as a hindrance to innovation and to adoption of new and current science.
Current validation methodologies are based on what is still a largely paper-based industry, although advances have been made in areas such as Electronic Batch Records (EBRs), Statistical Process Control (SPC), and Process Analytical Technology (PAT).
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Pharma 4.0 Paradigm Shifts
With the advent and implementation of Pharma 4.0 technologies and methodologies, these paradigms are shifting. Innovation becomes disruptive. Processes move from batch to continuous. Batch sizes move from bulk to personalized – the “batch size of one” for personalized medicine. The technology driver shifts to process digitalization, further digitization of process data, and incorporation of the digital enablers discussed in the prior article. Data management shifts to a distributed model and must account for data that move from the silo to everywhere throughout the value chain, from R&D to the bedside, incorporating field data from plant devices through the Industrial Internet of Things (IIoT) to patient data from medical devices using Edge AI. The process control strategy evolves to incorporate a dynamic, multivariate design space and to address a Holistic Control Strategy (HCS), ultimately shifting from algorithm-based, reactive process control to heuristic, predictive and, eventually, adaptive process control.
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Validation Challenges and Paradigm Shifts
Adoption of Pharma 4.0 requires digitalization of processes and development of digital maturity, which in turns requires deeper and more structured Product and Process Knowledge (PPK). Incorporation of modern digital technologies requires overcoming the traditional risk aversion, slow pace, and inertia of current practices. Much of the technology, including AI/ML, digital twins, and similar, is viewed as “bleeding edge”, which creates a sense of uncertainty.
In terms of closed vs distributed processing, what impact will there be when shifting from product testing prior to release to bedside manufacturing and delivery? In terms of bulk vs individualized medicine, what impact will there be when shifting from demonstrating product quality using AQL/sample testing in the plant to a “batch size of one”? How do we shift our understanding of validation as a demonstration that a CPP-based risk control strategy has been designed, implemented, and is effective to the demonstration of a holistic control strategy that addresses the full spectrum of product quality risks? And given our current approaches, how do we “validate” a process that has evolved from human-made process changes based on prescriptive process data to process-driven changes based on predictive and adaptive process data.
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Validation 4.0: The Goal
Validation 4.0 is a product of the acknowledgement that we can no longer apply 20th century thinking to 21st century technology and resources. As Pharma 4.0 adoption continues to increase, our validation practices must also change – not merely commensurately, but proactively.
Validation 4.0 intends to develop a holistic approach to validation that removes validation (facility, computer systems, process, etc.), functional (unit operations, functional areas, sites, etc.), data, and stakeholder (quality, engineering, operations, management, regulators) silos. Validation 4.0 intends to move away from validation paradigms that inhibit innovation, since to continue to inhibit innovation represents a risk to good business practice and, more importantly, represents a risk to delivering life-saving therapies to our patients. Finally, Validation 4.0 intends to develop a universal approach to validation that harmonizes all validation lifecycle processes and workstreams, facilitates science- and risk-based thinking and approaches, incorporates the Pharma 4.0 Operating Model, is enabled by Digital Maturity and Data Integrity by Design, and is aligned with, supports, and enables current and future innovations.
That’s why this article series began with a discussion about “What is Validation?”, posing a modified paradigm of validation in terms of defining product quality, defining the process, identifying process risks to product quality, designing a control strategy to mitigate identified process risks, designing and implementing that control strategy, and demonstrating that the control strategy is in place and is effective, ultimately resulting in a process that is documented and demonstrated to be in a state of control, reliably producing quality product. This paradigm is intended to help address the other, needed paradigm shifts and methodology changes needed to allow validation to enable and facilitate 21st century technology and resources, to the benefit of our patients.
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Conclusion
This article, the fourth and final in a series about Validation 4.0, provides an overview, definition, and discussion of Validation 4.0. This final article builds on the previous articles in the series:
Project Farma (PF) , a Precision For Medicine company, can help you implement these Validation 4.0 principles to support your efforts to deliver life-saving therapies to patients. If you are looking for project support, please contact us !
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2 个月Thanks for sharing Chip, commenting for better reach ??