Biomedical Engineering Reference
In-Depth Information
parameter/quality attribute, a total score for each parameter is calculated. Typically, there
is a natural break in the totals. The highest scores are considered highest priority, medium
scores are considered medium priority, and so on. The experimental strategies to address
the parameter/attribute are then defined.
Experimental strategies include failure mode and effects analysis (FMEA), one
factor at a time (OFAT), science of scale (SoS), and design of experiments (DOE).
Multiple experimental types may be used in a single focus area. The experimental
strategy is selected to gather enough information to provide results that can sufficiently
support the aim of the study. In the case of compounding (FA3), the highest ranking
scored experiments were viewed as a statistically designed experiment (DOE). The
factors of temperature, excipient and active concentration (amount from weighing
accuracy), and pH of the product were tested simultaneously to capture interactions
between these parameters and the effect on product quality.
10.3.4 Experimentation
Case Study DOE: Formulation Robustness and Formulation Design
Space.
The risk assessment scorecard in Table 10.1 identified excipient weight
accuracy and pH as two process parameters with a high-risk score, and a DOE strategy
was selected to address this. Formulation development studies define an optimal
composition that represents a point in the formulation space, but exact compositions
can be difficult to produce in large-scale processes. For example, preparation of large
volumes of buffers by weighing water and buffer salts may not yield the exact
composition as specified by the formulator. It is therefore important to understand the
robustness of the formulation to process-induced variations in composition parameters.
The range of composition parameters that the biologic can accept without significant
impact on all (critical and noncritical) quality parameters delineates the design space of
the formulation. An example of such a study is given below. It may be noted that while a
DOE approach to liquid formulation development has been commonly used (e.g.,
Refs [4-6]), robustness is not often taken into consideration.
For the case study discussed here, the composition for the biologic solution
formulation identified from formulation finding studies is given in Table 10.2.
TABL E 10.2. Formulation Identified as Optimal for a Biologic
Quantity (Molar Ratio
Compared to Active)
Component
Function
Active
1
Active ingredient
Buffer strength
20mM
Buffer
PH
5.5
—
Excipient A
1657
Tonicity adjuster/stabilizer
Excipient 1 (Surfactant)
1.1
Stabilizer
Excipient 2 (Chelator)
2.0
Stabilizer
Water for injection
q.s.
Solvent
