PROCESS LIFECYCLE VALIDATION - Risk Management Applications in Pharmaceutical and Biopharmaceutical Manufacturing - page 184

Process development and characterization is performed to establish a reliable
manufacturing process and to evaluate the effects of selected process parame-
ters and critical material attributes (CMAs) on process performance and product
quality. Quality by design (QbD) principles should be used when designing a
process. QbD is a risk- and science-based concept for the development of prod-
ucts and processes which recognize that quality cannot be tested into products but
should be built in by proper design. QbD principles increase product and process
understanding through the application of RAs and innovative tools and method-
ologies [18]. QbD results in robust manufacturing processes with boundaries that
can consistently deliver the desired product quality. The basis for the selection of
parameters or evaluation in process studies should include scientific rationale and
the use of risk-based approaches where relevant. The highest risk characteristics
(i.e., parameters with the greatest likelihood of product compromise) should be
evaluated first. All CPPs and CMAs for that unit operation or process step need
to be evaluated in PV studies. Screening experiments, fractional factorial design,
and response surface design studies can be used to determine CPPs [19,17].
Process development studies may be performed at laboratory, pilot, or man-
ufacturing scale. The cost of running experiments is exponentially higher at the
commercial scale compared to small scale. On the other hand, scaled-down sys-
tems can be completed independent of manufacturing operations. The studies
performed at the small scale must be representative of the manufacturing-scale
process in appropriate conditions and rationale, including equipment type/scale,
instrument calibration, and assay must be documented. Risk-based approaches
could be used to determine study type (e.g., generic or product-specific), number
of experiments, and scale. In the example given for roller compaction process of a
solid oral dosage product, the relative importance of inputs into the DoE is based
on an FMEA. Polymer concentration received the highest score and excipient
particle size the lowest, as shown in Figure 8.1. Hence, polymer concentration,
roller gap width, and roller gap force were subsequently evaluated in a DoE.
8.7.1 Risk-Based Study Design
Process input and output parameters must be identified for developing study
plans/protocols. Knowledge from other similar products and processes may be
leveraged to help design the study for a new product. At a minimum, the process
unit operations established during development (studies) should be defined before
the start of characterization or validation studies. pCQAs are identified using
scientific and clinical data before the start of formal PV [20]. When assessing
risks, all relevant data/information should be considered, such as product-specific
process development data, process knowledge from similar products (i.e., modular
data), manufacturing history (clinical and commercial), and scientific knowledge.
Process mapping is performed to document all input and output parameters.
Figure 8.2 shows the steps and considerations for PV in a risk-based approach. A
new study is not required if the process parameter range does not pose any risk to
product quality and patient safety. RAs can be used for study design, e.g., DOEs