Breakout sessions among participants focused on:
- The definitions and terms for describing process variation and process drift
- The most frequent causes of variation in pharmaceutical manufacturing
- Current strategies for monitoring and detecting process variability
- Evolutions in industry management approaches and the regulatory environment that could promote more proactive process improvement
throughout the product life cycle
- Impact of process drift on product bioavailability, safety, and efficacy.
The following section summarizes key outcomes of the breakout sessions.
Workshop participants recognized "process drift" as an "unintended, unexplained, or unexpected trend of measured process
parameter(s) and/or resulting product attribute(s) away from its intended target value in a time-ordered analysis over the
lifetime of a process or product."
When a substantial number of errors that occurred in pharmaceutical manufacturing were analyzed over a specified period, their
distribution was 40% due to recurring human errors, 30% due to recurring process errors, and 30% nonrecurring errors, as stated
by one of the speakers during the workshop. Human errors are due to inadequate training, poorly understood standard operating
procedures and processing parameters, lack of skill sets and procedural control, and inadequate resources. Other sources are
inadequate change management and risk management. Unsuitable equipment, deficient preventive maintenance, and inadequate equipment
calibration also lead to movement away from the normal process variability. Inadequate understanding of the inherent variability
in and inappropriate characterization of excipients, APIs, and other components can lead to unacceptable process variation
and can be one of the most complex areas to track during the life cycle of a pharmaceutical product.
Scientific rationale is needed to select variables on which to focus most when monitoring process drift. For raw materials,
the certificate-of-analysis (CoA) testing alone is insufficient to determine excipient variability. In comparison with commonly
used univariate analyses, use of multivariate analytical methods for assessing properties of raw materials, in-process materials,
and finished products by modeling relevant material attributes and process variables can support increased quality assurance.
However, appropriate education, training, and manufacturing process understanding is necessary to properly use these methods.
Analytical method drift should also be monitored.
Evolutions in industry management approaches could promote a more proactive process improvement throughout the life cycle
of a product. Justification to senior management is necessary to design and implement quality assurance concepts. Workshop
participants agreed that upper management must support the efforts to assure drug quality and understand the inherent costs
of poor quality. Estimation of the cost of failure can provide an indication of the ramifications and support the resources
needed. Better metrics are needed to quantify the risk–benefit ratio.
Participants also indicated that the regulatory landscape needs to be more predictable. Some also felt that the time and cost
to provide information to the regulators and receive approval for process improvements can be prohibitive.
Process drift has the potential to affect product performance for all types of dosage forms. More meaningful analytical tools
for understanding and detecting process drift are needed. Identification and use of improved input material measurements and
process information are necessary to improve the likelihood of alerting a manufacturer to process variability that may impact
product quality, including drug bioavailability. For example, to date, the best in vitro marker available to industry for drug bioavailability is dissolution. Even when in vitro–in vivo correlation is not conclusively established, significant emerging changes in product quality and manufacturing consistency
are detected by testing a compressed tablet for tablet disintegration and drug dissolution.
Overall, the participants felt that further work is needed to develop better methods that recognize and enhance understanding
of the effects of process drift on product quality and product performance.