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- Design of experiments (DoE) to develop and to optimize . . .
In this research, the authors used BBD to evaluate how these factors affected the responses entrapment efficiency, particle size, and cumulative drug permeation They observed that increasing lipid and span 80 or cholesterol and span 80 increased particle size
- Factors affecting response variables with emphasis on drug . . .
The outcome variables were entrapment efficiency, drug loading, and particle size As seen earlier, a quadratic polynomial equation helps predict the relationship between independent and outcome variables
- Quality by Design (QbD) and Design of Experiments (DOE) as a . . .
Six input variables were considered: C12-200:mRNA weight ratio, phospholipid type and phospholipid, C12-200, cholesterol, and PEG molar contents The output variables were encapsulation efficiency (%EE), particle size, polydispersity index (PDI), and EPO serum concentration
- Screening the statistical impact of some independent . . .
The present study provides the insight of statistical aspects of various independent variables like Tf-PLGA Curcumin ratio, stirring speed and emulsifying concentration over dependent variables
- Application of Box–Behnken design and desirability function . . .
Among the various techniques of response surface methodology (RSM), Box–Behnken design (BBD) is a suitable approach for ascertaining the effects of formulation ingredients variables (independent factors) and their associated effect on the response variables (dependent factors)
- Optimization of nanostructured lipid carriers: understanding . . .
RSM plots showing multi-response situations when the independent variables (amount of oleic acid, amount of glycerol monostearate, and concentration of Poloxamer) are simultaneously manipulated to determine the responses (particle size, entrapment efficiency, and percentage of cumulative drug release) in the optimization of simvastatin-loaded
- 11. 2. 2 - Box-Behnken Designs | STAT 503 - Statistics Online
The central composite design is used more often but the Box-Behnken is a good design in the sense that you can fit the quadratic model It would be interesting to look at the variance of the predicted values for both of these designs
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