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granule properties, granulation time followed by wetting rate and
jacket temperature have an important infl uence on the product/
intermediate quality. Statistically signifi cant CPPs were identifi ed
for granule hardness, granule density, and granule particle size.
These granule properties were also identifi ed as contributing to the
dissolution release characteristics. Dissolution modeling and
prediction was achieved within the DoE structure.
Example
2
Asymmetrical factorial design was used for screening of high shear
mixer melt granulation process variables using an asymmetrical
factorial design (Voinovich et al., 1999). The factors under
investigation were binder grade, mixer load, presence of the
defl ector (all analyzed at 2 levels), binder concentration, impeller
speed, massing time, type of impeller blades (these 4 at 3 levels),
and jacket temperature (considered at 4 levels). Two granule
characteristics were analyzed: the geometric mean diameter and
the percentage of particles fi ner than 315 μm. The factorial
arrangement 2
3
3
4
4
1
//25 was used, where 25 represents the
number of runs. Asymmetrical factorial design allowed reduction in
the number of runs from 2592 to 25. In addition, this technique
permitted the selection of the factor levels, which have the major
'weight' on the 2 granule characteristics under study. Two additional
trials were performed to attest the screening validity. The weight of
each factor level was estimated by means of the least squares
method.
Example
3
The Plackett-Burman design was used to study the effects of 11
different factors on stabilization of multicomponent protective
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