Design expert

Manufactured by Stat-Ease

Sourced in United States

Design Expert is a statistical software package for experimental design, data analysis, and optimization. It provides a user-friendly interface for creating, running, and analyzing designed experiments. The software offers a range of experimental design techniques, including factorial, response surface, mixture, and screening designs.

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Lab products found in correlation

Jmp pro, by SAS Institute (2 mentions) Prism 5, by GraphPad (2 mentions) Spss ver 17, by IBM (1 mentions) Spss software 17, by IBM (1 mentions) Labsolutions software, by Shimadzu (1 mentions) Origin 7.5 software for windows, by OriginLab (1 mentions) Pasw statistics 18, by IBM (1 mentions) Spss software 27, by IBM (1 mentions) Spss v24, by IBM (1 mentions) Sigmaplot 12, by Grafiti LLC (1 mentions) Sucrose, by Thermo Fisher Scientific (1 mentions) R software, by Posit (1 mentions) Masshunter workstation data acquisition, by Agilent Technologies (1 mentions) Spss version 18, by IBM (1 mentions) Statistica software, by StatSoft (1 mentions) Origin 2018, by OriginLab (1 mentions) Origin 8, by OriginLab (1 mentions) Spss ver 16, by IBM (1 mentions) Kta pure 25, by Cytiva (1 mentions) Eurostar, by IKA Group (1 mentions)

211 protocols using design expert

Optimizing DOM-Loaded Ethosomal Suspensions

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A complete 2¹, 5¹ multi-level factorial design was created by Design Expert^® software, version 12.0 (Stat Ease, Inc., Minneapolis, MN) to determine the effect of different variables on DOM-loaded ethosomal suspensions using the low experimental runs. In this chosen design, the effects of two independent variables specifically, lecithin concentration (1st factor) at two levels (2% and 3%) and type of additives (2nd factor) at five levels (none, oil A (Labrafac^®), oil B (oleic acid), tween 80, and span 60) on five responses as namely, vesicular size (PS), polydispersity index (PDI), electrical double layer ZP, % efficiency of drug entrapment (%EE), and % cumulative drug release after 6 h (Q6h) were estimated (Table 1). The experimental design covered all probable formulations for incorporation of DOM-loaded into ethosomal suspensions as shown in Table 2. The experimental data were evaluated for significance by the analysis of variance (ANOVA) test using Design Expert^® software (Stat Ease, Inc., Minneapolis, MN). Desirability was calculated for selection of optimum formulation after insertion of desired outcomes. The criterion set for deciding the optimized formulation was accomplishment of the least PS, PDI and the highest %EE, ZP, and Q6h.

Sakran W., Abdel-Rashid R.S., Saleh F, & Abdel-Monem R. (2022). Ethosomal gel for rectal transmucosal delivery of domperidone: design of experiment, in vitro, and in vivo evaluation. Drug Delivery, 29(1), 1477-1491.

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Multivariate Optimization and Modeling of Experimental Data

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Both the statistical regression analysis of the RCCD matrix with the experimental results and also the analysis of variance (ANOVA) were accomplished using the statistical software package Design-Expert (version 12, Stat-Ease, Minneapolis, USA) (Design-Expert/">https://www.statease.com/software/Design-Expert/). The ANN topology was set up using JMP 11 software (JMP, Version 11 SAS Institute Inc., Cary, NC, 1989–2019), which enables training, validating, and testing using experimental data with several hidden neurons. Training of ANN was performed using 17 randomly selected runs by the software, whereas the other 9 runs were used to check the validity of the trained ANN model. To enhance the prediction accuracy of both models, experiments of RCCD were repeated twice, each with three replicates. The mean of each experimental run was calculated.

Saber W.I., El-Naggar N.E., El-Hersh M.S., El-khateeb A.Y., Elsayed A., Eldadamony N.M, & Ghoniem A.A. (2021). Rotatable central composite design versus artificial neural network for modeling biosorption of Cr6+ by the immobilized Pseudomonas alcaliphila NEWG-2. Scientific Reports, 11, 1717.

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Optimizing Laccase Production via OFAT-RSM

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The physicochemical parameter that had influencing effect on the production of laccase were identified using the OFAT method, and levels of each parameter were chooses in RSM design using Central Composite Design (CCD) in Design Expert software (Design Expert, Stat-Ease Inc, version 8.0.6.1). Five different levels of every factor were experimented in set of 30 experiments. The highest significance of each parameter acquired from optimization using OFAT was considered as the zero value in RSM. The minimum and maximum ranges for the parameters were; Factor: 1 (Temperature) 24 -28°C, Factor: 2 (pH) 4-7, Factor: 3 (Moisture content) 65-80% and Factor: 4 (Inoculum) 5-10% (w/w). Experiments of all the permutations were performed in 100 g SSF system. The arithmetical association of the selfdetermining factors and the response (laccase activity) were estimated by the second-degree polynomial equation.

Sharma S., & Murty D.S. (2021). Enhancement of Laccase Production by Optimizing the Cultural Conditions for Pleurotus sajor-caju in Solid-State Fermentation. Journal of Pure and Applied Microbiology, 15(2), 958-967.

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Statistical and Machine Learning Analysis

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The software, Design Expert (version 13, Stat-Ease, Minneapolis, USA), was utilized to set up the CCFCD design matrix and perform the statistical examinations. The machine learning procedure, construction of the ANN topology, and statistical examinations were performed with aid of the software package; JMP pro, version 16.2 (JMP, SAS Institute Inc., Cary, NC), through which the training, validating, and testing processes were performed.

El-Naggar N.E., Bashir S.I., Rabei N.H, & Saber W.I. (2022). Innovative biosynthesis, artificial intelligence-based optimization, and characterization of chitosan nanoparticles by Streptomyces microflavus and their inhibitory potential against Pectobacterium carotovorum. Scientific Reports, 12, 21851.

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Optimizing TiO2 Nanoparticle Synthesis via Response Surface Methodology

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The effect of reaction conditions on the TiO₂ NP size via response surface methodology (RSM) through central composite inscribed (CCI) design was investigated using the cell-free filtrate of the Halomonas sp. RAM2 optimized growth [70 (link)]. Three independent variables using Design Expert (Version 11 Stat-Ease Inc., Minneapolis, MN, USA) were applied to investigate the effects of the starting TiO₂ concentration (A), pH (B) of the cell-free filtrate, and the reaction duration (C) on TiO₂ NPs size (Table 3). The following polynomial equation fits the experimental results:

Y = β_{0} + β_{1} X_{1} + β_{2} X_{2} + β_{3} X_{3} + β_{12} X_{1} X_{2} + β_{13} X_{1} X_{3} + β_{23} X_{2} X_{3} + β_{11} X_{11}^{2} + β_{22} X_{22}^{2} + β_{33} X_{33}^{2}

where Y represents the response (TiO₂ NPs size (nm)), β₀ is constant, β₁, β₂, and β₃ is linear coefficients, β₁₂, β₁₃, and β₂₃ is cross product coefficients, β₁₁, β₂₂, and β₃₃ is quadratic coefficients.Table 3

Experimental independent variables and their coded levels for the central composite design

Name	Code	Levels of coded variables
		− α	− 1	0	+ 1	+ α
TiO₂ concentration (M)	A	0.005	0.0141214	0.0275	0.0408786	0.05
pH	B	5	5.8	7	8.2	9
Reaction duration (min)	C	60	72	90	107	120

The average size of TiO₂ NPs was estimated using XRD analysis and the Scherrer’s formula. The model accuracy was determined by the coefficient of R². The P-value for the significant model terms was set at 95%.

Metwally R.A., El Nady J., Ebrahim S., El Sikaily A., El-Sersy N.A., Sabry S.A, & Ghozlan H.A. (2023). Biosynthesis, characterization and optimization of TiO2 nanoparticles by novel marine halophilic Halomonas sp. RAM2: application of natural dye-sensitized solar cells. Microbial Cell Factories, 22, 78.

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Optimizing Cultural Factors Using CCD

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The central composite design (CCD) was used to analyze the interaction among six cultural factors and deter- mine their optimal values (Table 1). The modeling was conducted using Design Expert (version 6.0.8, Stat-Ease, Inc., USA) statistical software including analysis of variance (ANOVA) that generated 90 experiments to obtain the interactions between the process variables and the response. To validate the statistical model, an experiment under the optimal condition predicted by the model was conducted and the actual experimental value was compared with the predicted one.

Farahat M.G. (2020). Enhancement of ��-Cyclodextrin Production and Fabrication of Edible Antimicrobial Films Incorporated with Clove Essential Oil/��-cyclodextrin Inclusion Complex. Microbiology and Biotechnology Letters, 48(1), 12-23.

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Optimizing Nanoparticle Formulations with Taguchi Design

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Taguchi’s L9 orthogonal array experimental design was used to optimize the formulation parameters of TPL-SFNPs and CL-SFNPs. A 3-factor, 3-level design was employed for studying the interaction and quadratic effects of the formulation variables. The initial concentrations of SF, TPL and CL and volume ratio of organic/SF solution for formulation optimization were selected based on preliminary experiments (data not shown). The three factors and their levels selected for formulation optimization are shown in Table S1. A Design-Expert^® (Version 10.1, Stat-Ease Inc., USA) software was used for analyzing the results.

Ding B., Wahid M.A., Wang Z., Xie C., Thakkar A., Prabhu S, & Wang J. (2017). Triptolide and Celastrol Loaded Silk Fibroin Nanoparticles Show Synergistic Effect against Human Pancreatic Cancer Cells. Nanoscale, 9(32), 11739-11753.

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Optimizing Nanoparticle Formulation via CCD

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All hydrodynamic diameter and %Inhibition data are presented as average and standard deviation (SD). According to the experimental design, CCD was constructed using statistical software (Design-Expert^®, version 10.0.5.0, Stat-Ease, Inc., Minneapolis, MN, USA). The quadratic model was firstly fitted and reduced to a two-factor interaction and linear models corresponding to the significant p-value (< 0.05) and insignificant Lack-of-fit (p-value > 0.05) from analysis of variance (ANOVA). The significant model was accepted when the p-value of the model was less than 0.05, with a high goodness of fit (R²), and no correlation in the residual plots and the residuals were normally distributed.

Saokham P., Burapapadh K., Praphanwittaya P, & Loftsson T. (2020). Characterization and Evaluation of Ternary Complexes of Ascorbic Acid with γ-Cyclodextrin and Poly(vinyl Alcohol). International Journal of Molecular Sciences, 21(12), 4399.

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Optimizing Roasting Conditions for Bioactive Compounds

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Seeds were roasted using developed experimental runs from the central composite design of the RSM (Design-Expert version 8.3.0.1, Stat-Ease, Minneapolis, MN, USA). The upper and lower boundaries of roasting conditions used were 200°C for 40 min and 110°C for 10 min, respectively. The effects of the two independent variables [(roasting temperature (A) and roasting time (B)] on five responses [steroid content estimation, total phenolics (TP), total tannins (TT), total cardiac glycoside, and total flavonoid (TF)] were evaluated as shown in Table 1. The models with statistically significant parameters (P≤0.05) were considered, optimized using numerical tools and the desirability.
The second order polynomial equation (Eq. 1) was used to determine the effect of independent variables (process variables) on the responses.

Ajatta M.A., Akinola S.A., Otolowo D.T., Awolu O.O., Omoba O.S, & Osundahunsi O.F. (2019). Effect of Roasting on the Phytochemical Properties of Three Varieties of Marble Vine (Dioclea reflexa) Using Response Surface Methodology. Preventive Nutrition and Food Science, 24(4), 468-477.

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ANOVA and Duncan's Test for Treatment Comparison

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One-way analysis of variance (ANOVA) and Duncan’s multiple range test were conducted to confirm the statistical differences between treatment groups by statistical software package Design Expert (Stat-Ease, Inc Minneapolis, MN, USA). All the operated experiments were conducted in triplicate and the obtained data were showed as mean ± standard deviation (SD). The obtained results were considered statistically significant when the p-value was <0.05. Stat-Ease Design Expert v7.0.0 was also used to determine the significant factors among all studied factors.

El-Abeid S.E., Ahmed Y., Daròs J.A, & Mohamed M.A. (2020). Reduced Graphene Oxide Nanosheet-Decorated Copper Oxide Nanoparticles: A Potent Antifungal Nanocomposite against Fusarium Root Rot and Wilt Diseases of Tomato and Pepper Plants. Nanomaterials, 10(5), 1001.

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