The pharmaceutical industry's recent emphasis on continuous improvement, operational excellence, and process analytical technology
has motivated us to evaluate the basic tenets of our approach to quality. Historically, the ability to ensure that a drug
meets its intended form, fit, and function has been achieved through the application of the quality infrastructure, i.e.,
standard operating procedures, policies, specifications; qualification or validation, i.e., commissioning, installation qualification
(IQ), operational qualification (OQ), performance qualification (PQ), process validation; and testing, i.e., in-process and
final release. However, despite these processes, the number of drug recalls continues to rise, escalating from 176 in 1998
to 354 in 2002, according to the US Center for Drug Evaluation and Research.1
The use of regulations as a primary means of ensuring product quality began to decline in early 2000, when industry pushed
back on FDA's Part 11 compliance requirements for electronic signatures and electronic data exchange, challenging the cost
and effort associated with implementation, versus the actual benefit to product quality. Today, however, industry and regulatory
agencies are moving toward a more scientific approach to ensuring product quality.
The International Conference on Harmonization (ICH) Q8 and Q9 guidance documents2,3 , for example, define a scientific approach to process characterization, advocating a quality by design framework. Risk management
is an integral part of this approach.
Similarly, the US FDA's "GMPs for the Twenty-First Century" initiative focused on quality by design, risk management, continuous
process improvement, and quality systems. Rolled out in 2004, this initiative challenged industry's traditional approaches
to ensuring product quality by encouraging employees to look beyond traditional inspection methodologies for ensuring product
performance. The early process and product characterization emphasized in the quality-by-design and risk-management approaches
do not inherently conflict with validation. On the contrary, by deepening the level of scientific understanding of a manufacturing
process, the approaches ensure that a process is well understood before it is considered "validated." Methods that involve
continuous improvement and real-time control, however, do pose a significant question: Are these quality methods inconsistent
with the basic tenets of validation that have served as the backbone of the industry's quality structure for so many years?
Once you have "validated" a manufacturing process, how much can you improve it—through real-time control or any sort of continuous
improvement step incorporated into Lean, Six Sigma, etc.—without having to file manufacturing supplements with FDA? How much
of an impediment are those filing requirements?
THE VALIDATION PARADIGM
The challenge of validation is that it has been viewed as a necessary evil—a regulatory activity that cannot be avoided when
manufacturing regulated products. The effort and cost associated with validation continue to escalate as industry and regulatory
groups increase their understanding of pharmaceutical processes and identify an increasing number of process variables that
must be controlled. Biotech adds another layer of complexity by introducing the qualified pilot or intermediate-scale model
as an integral component of the validation equation.4
The prohibitive cost of characterization studies at full scale requires us to establish clear, scientific arguments to show
how process development studies relate to full-scale validation lots. The complexity of biotech processes demands an even
higher level of scientific argument. As we increase our understanding of biopharmaceutical processing, the value associated
with traditional validation diminishes, and industry responds accordingly.
The integration of equipment validation and process validation provided incentive to measure the capability of our processes
and analytical methods. However, somewhere along the way, the incentive for validation shifted from a need to measure processes,
to a need to satisfy a regulatory requirement as quickly and as cheaply as possible.