Biomedical Engineering Reference
In-Depth Information
13.5.1 Process Understanding
Process understanding, or rather an understanding of the interdependencies between the
inputs and process parameters, the target product profile and quality attributes, is
fundamental to both QbD and PAT. A Standard Guide to Process Understanding is
being developed by the ASTM E55.01 subcommittee to provide a better definition and
clearer common vocabulary for this important topic [29].
A process is considered well understood when “all critical sources of variability are
identified and explained, the effect on quality attributes can be accurately and reliably
predicted based on the inputs to the process, and the process capability for critical quality
attributes meets the required acceptance levels.” The standard recognizes that learning
continues throughout the life cycle of a product and that additional knowledge will
become available as additional experience is gathered or as new PAT tools are brought to
bear. Typically, process information is first gathered through the appropriate small-scale
models and experience with similar processes, but knowledge and understanding of the
process develops as experience is gained through various scales and stages and
modifications through and beyond commercialization.
Process knowledge exists in various states, as indicated in Table 13.3.
The most basic level of understanding, descriptive knowledge, is simply a descrip-
tion of what is done and is usually displayed as high-level flowcharts and descriptive text.
In this case the focus is on compliance and any excursions take the process into unknown
territory. Correlative knowledge is achieved when the interrelationships between vari-
ables are known but without understanding the underlying mechanisms. Correlative
knowledge can be improved through, for example, risk analysis. Causal knowledge is
achieved when there is significant scientific knowledge on the underlying causes of the
interrelationships between variables. There is a level of awareness to the criticality of
variables and approaches to their control through PAT tools. Mechanistic knowledge is
based on understanding how causal relationships occur. It is typically achieved through
multivariate analysis and executed through multivariate statistical controls. At this stage
TABL E 13.3. Categories of Process Knowledge from Lowest to Highest State
of Understanding
Descriptive knowledge
What is occurring
Derived from observation and reflects
basic facts, focus on compliance
Correlative knowledge
What is correlated
to what
Correlation between inputs and outputs,
may be univariate, FMEA
Causal knowledge
What causes what
Significant scientific knowledge
established, critical variables
understood, PAT controls
Mechanistic knowledge
How
Multivariate tools and controls
employed, solid basis for scale-up and
tech transfer
First principles
understanding
Why
Fundamental theoretical understanding,
prediction of behavior, design in
performance, and process innovation
