Experimental design and multiple response optimization. Using the desirability function in analytical methods development

In the current paper, and for the first time, spectrophotometry coupled with a set of factorial designs was executed as a new tool for investigating the interaction between p-synephrine (p-SY) and p-chloranil (p-CHL). Two types of complexes were observed as a result of this interaction. The first complex, an intermolecular charge transfer complex, was measured at 452 nm, while the second, an intramolecular charge transfer complex, was measured at 536 nm. A chemometric assisted screening and optimization of the absorbance at the two wavelengths was scrutinized. As a screening procedure, a 2-level full factorial design (2 k -FFD) was employed. Method variables, such as reaction temperature, heating time, reagent volume, and solvent type were considered and the response was measured at the individual wavelengths. With the help of Pareto analysis, and ANOVA testing (following a response transformation employing Box-Cox treatment), variables ascertained to be significant (p < 0.05) were selected.Significant factors were carefully adjusted, exploiting a response surface methodology (RSM) with a face-

show abstract

“…3. 32 As shown in Fig. 4, a better normal distribution was obtained aer running Box-Cox transformation, 33 where:…”

Section: Response Transformation and Modellingmentioning

confidence: 92%

“…Domains for each factor were redened and carefully re-adjusted. In case of Y 1 , reaction temperature was kept in the range of [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] C mL, and C ¼ 40 min. Both responses were initially described using a quadratic polynomial model.…”

Section: Response Surface Designmentioning

confidence: 99%

Interaction of p-synephrine with p-chloranil: experimental design and multiple response optimization

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Derringer and Such developed this function in 1980 33 and applied in areas of industry and sciences. Review paper by Candioti et al 34 had explained how to carry out these experiments and described its application with many examples. Shortly, when more responses have been pursued, then optimization will be achieved by changing multiple responses into single and merging the singular responses into composite function.…”

Section: Methods Optimizationmentioning

confidence: 99%

Untitled

2017

IJPSR

View full text Add to dashboard Cite

Paper presents a novel high performance liquid chromatography method development, optimization, validation and application of determining blonanserin in bulk drug, its formulation, human serum and in the presence of its degradation products. Selection of important factors which may influence separation were concluded: percentage of acetonitrile in the mobile phase, the percentage of orthophosphoric acid in aqueous phase and flow rate. Factors selected were altered in accordance to Box-Behnken design plan and investigation in factors having significant influence on separation were executed. Finally, the choicest values from solution offered of investigated factors were 43 % of acetonitrile in the mobile phase, 0.03% orthophosphoric acid in water and flowrate of 0.75 ml/min. The method validation was performed according to International Conference on Harmonisation guideline acceptance criteria for robustness, linearity, selectivity, precision and accuracy. Quantitative and qualitative system responses have not significantly affected by little variations in chromatographic parameters, which demonstrates robustness of the method. Limits of quantification and detection for blonanserin was calculated. Method shows excellent linearity, which was confirmed by r 2 = 0.9991 over the concentration range of 5 -50 µg/ml. Accuracy was calculated by recovery experiment and found to be in range 99.44-100.76 %. Precision was carried out at different levels: analysis repeatability, injection repeatability and intermediate precision and was found well under acceptable criteria. Furthermore, the applicability of method was analysed in real time sample analysis of blonanserin in its commercial pharmaceutical preparations and in-vitro human serum samples.

show abstract

“…Desirability always takes values in the range of 0 to 1, where 0 is an undesirable response, and 1 represents an ideal response. For more or less desirable responses desirability function takes intermediate values [27]. Each obtained response has an individual desirability value ranging from 0 to 1.…”

Section: Optimization Of the Microfiltration Process Using Desirabilimentioning

confidence: 99%

Data-driven Modelling of Microfiltration Process with Embedded Static Mixer for Steepwater from Corn Starch Industry

Šereš

Dokić

Ikonić

et al. 2017

Period. Polytech. Chem. Eng.

View full text Add to dashboard Cite

Experimental design and multiple response optimization. Using the desirability function in analytical methods development

Cited by 886 publications

References 64 publications

Interaction of p-synephrine with p-chloranil: experimental design and multiple response optimization

Interaction of p-synephrine with p-chloranil: experimental design and multiple response optimization

Untitled

Data-driven Modelling of Microfiltration Process with Embedded Static Mixer for Steepwater from Corn Starch Industry

Contact Info

Product

Resources

About