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of the best formulation conditions to optimize drug release rate.
The experimental values obtained from the optimized formulation
highly agreed with the predicted values.
Example
7
A modifi ed co-acervation or ionotropic gelation method was used to
produce gatifl oxacin-loaded submicroscopic nanoreservoir systems
(Motwani et al., 2008). It was optimized using DoE by employing a
3-factor, 3-level Box-Behnken statistical design. Independent
variables studied were the amount of the bioadhesive polymers:
chitosan, sodium alginate, and the amount of drug in the
formulation. The dependent variables were the particle size, zeta
potential, encapsulation effi ciency, and burst release. Response
surface plots were drawn, statistical validity of the polynomials
was established, and optimized formulations were selected by
feasibility and grid search. An example of the response surface
plot, showing effect of chitosan and sodium alginate concentration
on encapsulation effi ciency, is displayed in Figure 3.4.
Objective function for the presented study was selected as
maximizing the percentage encapsulation effi ciency, while
minimizing the particle size and percentage burst release. BBD
was used to statistically optimize the formulation parameters and
evaluate the main effects, interaction effects, and quadratic
effects of the formulation ingredients on the percentage
encapsulation effi ciency of mucoadhesive nano-reservoir systems.
A 3-factor, 3-level design was used to explore the quadratic
response surfaces and for constructing second-order polynomial
models. This cubic design is characterized by a set of experimental
points (runs) lying at the midpoint of each edge of a multidimensional
cube and center point replicates (n = 3), whereas the 'missing
corners' help the experimenter to avoid the combined factor
extremes. A design matrix comprising of 15 experimental runs was
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