Abstract
Quality by design (QBD) refers to the achievement of certain predictable quality with desired and predetermined specifications. A very useful component of the QBD is the understanding of factors and their interaction effects by a desired set of experiments. The present project deals with a case study to understand the effect of formulation variables of nanoemulsified particles of a model drug, cyclosporine A (CyA). A three-factor, three-level design of experiment (DOE) with response surface methodology (RSM) was run to evaluate the main and interaction effect of several independent formulation variables that included amounts of Emulphor El-620 (
X
1), Capmul MCM-C8 (
X
2) and 20% (w/w) CyA in sweet orange oil (
X
3). The dependent variables included nanodroplets size (
Y
1), nanoemulsions turbidity (
Y
2), amounts released after 5 and 10
min (
Y
3,
Y
4), emulsification rate (
Y
5) and lag time (
Y
6). A desirability function was used to minimize lag time and to maximize the other dependent variables. A mathematical relationship,
Y
5
=
9.09
−
0.37
X
1
+
0.37
X
2
−
0.45
X
3
+
0.732
X
1
X
2
−
0.62
X
1
X
3
+
0.3
X
2
X
3
+
0.02
X
1
2
−
0.28
X
2
2
+
0.471
X
3
2
(
r
2
=
0.92), was obtained to explain the effect of all factors and their colinearities on the emulsification rate. The optimized nanodroplets were predicted to yield
Y
1,
Y
2,
Y
3,
Y
4,
Y
5 and
Y
6 values of 42.1
nm, 50.6
NTU, 56.7, 107.2, 9.3%/min and 3.5
min, respectively, when
X
1,
X
2, and
X
3 values were 36.4, 70 and 10
mg, respectively. A new batch was prepared with these levels of the independent variables to yield
Y
1–
Y
6 values that were remarkably close to the predicted values. In conclusion, this investigation demonstrated the potential of QBD in understanding the effect of the formulation variables on the quality of CyA self-nanoemulsified formulations.