Fused Deposition Modelling (FDM) is one of the layer-based technologies that fall under the umbrella term \"Additive Manufacturing\", where the desired part is created through the successive layer-by-layer addition process with high accuracy using computer-aided design data. Additive manufacturing technology, or as it is commonly known, 3D (three-dimensional) printing, is a rapidly growing sector of manufacturing that is incorporated in automotive, aerospace, biomedical, and many other fields. This work explores the impact of the Additive Manufacturing process on the mechanical proprieties of the fabricated part. To conduct this study, the 3D printed tensile specimens are designed according to the ASTM D638 standards and printed from a digital template file using the FDM 3D printer Raise3D N2. The material chosen for this 3D printing parameter optimization is Polylactic acid (PLA). The FDM process parameters that were studied in this work are the infill pattern, the infill density, and the infill cell orientation. These factors\' effects on the tensile behavior of printed parts were analyzed by the design of experiments method, using the statistical software MINITAB2020.

This work is focused on performing a quantitative assessment of the environmental impacts associated with an organic synthesis reaction, optimized using an experimental design approach. A nucleophilic substitution reaction was selected, employing vanillin as the substrate, a phenolic compound widely used in the food industry and of pharmaceutical interest, considering its antioxidant and antitumoral potential. To carry out the reaction, three different solvents have been chosen, namely acetonitrile (ACN), acetone (Ace), and dimethylformamide (DMF). The syntheses were planned with the aid of a multivariate experimental design to estimate the best reaction conditions, which simultaneously allow a high product yield and a reduced environmental impact as computed by Life Cycle Assessment (LCA) methodology. The experimental results highlighted that the reactions carried out in DMF resulted in higher yields with respect to ACN and Ace; these reactions were also the ones with lower environmental impacts. The multilinear regression models allowed us to identify the optimal experimental conditions able to guarantee the highest reaction yields and lowest environmental impacts for the studied reaction. The identified optimal experimental conditions were also validated by experimentally conducting the reaction in those conditions, which indeed led to the highest yield (i.e., 93%) and the lowest environmental impacts among the performed experiments. This work proposes, for the first time, an integrated approach of DoE and LCA applied to an organic reaction with the aim of considering both conventional metrics, such as reaction yield, and unconventional ones, such as environmental impacts, during its lab-scale optimization.

BACKGROUND: Factorial design is a simple, yet elegant method to investigate the effect of multiple factors and their interaction on a specific response simultaneously. Hence, this type of study design reaches the best optimization conditions of a process. Although the interaction between the variables is widely prevalent in cell culture procedures, factorial design per se is infrequently utilized in improving cell culture output. Therefore, we aim to optimize the experimental conditions for generating mature bone marrow-derived dendritic cells (BMDCs). Two different variables were investigated, including the concentrations of the inducing factors and the starting density of the bone marrow mononuclear cells. In the current study, we utilized the design of experiments (DoE), a statistical approach, to systematically assess the impact of factors with varying levels on cell culture outcomes. Herein, we apply a two-factor, two-level (22) factorial experiment resulting in four conditions that are run in triplicate. The two variables investigated here are cytokines combinations with two levels, granulocyte-macrophage colony-stimulating factor (GM-CSF) alone or with interleukin-4 (IL4). The other parameter is cell density with two different concentrations, 2 × 106 and 4 × 106 cells/mL. Then, we measured cell viability using the trypan blue exclusion method, and a flow cytometer was used to detect the BMDCs expressing the markers FITC-CD80, CD86, CD83, and CD14. BMDC marker expression levels were calculated using arbitrary units (AU) of the mean fluorescence intensity (MFI).
RESULTS: The current study showed that the highest total viable cells and cells yield obtained were in cell group seeded at 2 × 106 cells/mL and treated with GM-CSF and IL-4. Importantly, the expression of the co-stimulatory molecules CD83 and CD80/CD86 were statistically significant for cell density of 2 × 106 cells/mL (P < 0.01, two-way ANOVA). Bone marrow mononuclear cells seeded at 4 × 106 in the presence of the cytokine mix less efficiently differentiated and matured into BMDCs. Statistical analysis via two-way ANOVA revealed an interaction between cell density and cytokine combinations.
CONCLUSIONS: The analysis of this study indicates a substantial interaction between cytokines combinations and cell densities on BMDC maturation. However, higher cell density is not associated with optimizing DC maturation. Notably, applying DoE in bioprocess designs increases experimental efficacy and reliability while minimizing experiments, time, and process costs.

In this paper, a pelletizing method has been researched to enhance the subsequent iron-making process applying Guisha limonite, with advantages including large reserves and low price. The purpose is to provide an alternative for the sinter, thus reducing the greenhouse gas emission during the iron-making process. The response surface method is used to optimize the experimental design of the pelleting process. A multivariate regression model for estimating the compressive strength of pellets was developed using Box-Behnken experimental methodology, where the relevant factors were the roasting temperature, pellet diameter, and bentonite content. The maximum influencing factors of each experimental design response are determined using analysis of variance (ANOVA). Under optimum conditions, the compressive strength of pure limonite pellets is 2705 N, similar to the response goal value of 2570.3 N, with a relative error of 5.20%. Since the high-grade iron ore resources are depleted, the comprehensive utilization of ore resources is becoming increasingly important. The aim of this paper was to provide a valuable technical foundation for lignite pellet-roasting processes in the iron and steel industries, since steel companies is increasing its imports of Guisha limonite.

Oleogels (defined as structured solid-like materials with a high amount of oil entrapped within a three-dimensional network of gelator molecules) represent a healthy alternative to fats that are rich in saturated and trans fatty acids. Given its fatty acids composition (oleic, linoleic, and linolenic acids), olive oil is an excellent candidate for the use of oleogels in the food industry. In this study, a D-optimal mixture design was employed to optimize the replacement of butter with olive oil-based oleogel in a type of sponge cake formulation: the plum cake. In addition, emulsifiers and whey proteins were used as recipe ingredients to extend the product\'s shelf life by delaying staling phenomena and mold growth. In the experimental design, oleogel, emulsifier, and whey protein variables were set as the ingredients that change in specific ranges, while hardness, porosity, water activity, and moistness were used to characterize the obtained formulations. The experimental data of each response were fitted through polynomial regression models with the aim of identifying the best plum cake formulation. The results revealed that the best mixture was the formulation containing 76.98% olive oil-based oleogel, 7.28% emulsifier E471, and 15.73% whey protein. We stored the optimized plum cake for 3 months at room temperature and then checked for any hardness and moistness changes or mold spoilage.

The objective of this study was to explore the possible use of a new combination of two excipients, i.e., nanocrystalline cellulose (NCC) and macroporous silica (MS), as matrix materials for the compounding of dry emulsion systems and the effects these two excipients have on the characteristics of dry emulsion powders produced by the spray drying process. A previously developed liquid O/W nanoemulsion, comprised of simvastatin, 1-oleoyl-rac-glycerol, Miglyol 812 and Tween 20, was employed. In order to comprehend the effects that these two matrix formers have on the spray drying process and on dry emulsion powder characteristics, alone and in combination, a DoE (Design of Experiment) approach was used. The physicochemical properties of dry emulsion samples were characterised by atomic force microscopy, scanning electron microscopy, mercury intrusion porosimetry, energy-dispersive X-ray spectroscopy and laser diffraction analysis. Additionally, total release and dissolution experiments were performed to assess drug release from multiple formulations. It was found that the macroporous silica matrix drastically improved flow properties of dry emulsion powders; however, it partially trapped the oil-drug mixture inside the pores and hindered complete release. NCC showed its potential to reduce oil entrapment in MS, but because of its rod-shaped particles deposited on the MS surface, powder flowability was deteriorated.

In the current study, we demonstrate a structured approach to downstream process development for spray dried amorphous solid dispersions. Direct compression is generally not suitable due to typically poor flow of spray dried powders in tablets. Roller compaction (RC) is therefore the method of choice to enable spray dried dispersion downstream processing. Here, a structured experimental design of RC process parameters was used. The objective was to identify process conditions that lead to improved powder flow without compromising tablet robustness. Ten blends were compacted using different process parameters, and subsequently compressed into tablets. The impact of process parameters on granules and tablet properties was analyzed. We demonstrate that compaction force, gap and mesh aperture have major impact on RC outcomes. A combination of large gap and low force was identified as optimum combination of RC process parameters leading to powder flow improvement that could guarantee low tablet weight variation and at the same prevented loss of blend compressibility.

This study reports a fully validated HPLC-UV (High Performance Liquid Chromatography- Ultra Violet) method for quantitative estimation of Rufinamide (RUFI), an antiepileptic drug, in rat plasma and brain matrices. A response surface methodology based Box Behnken experimental design, using the principles of Design of Experiments (DoE), was employed to optimize critical chromatographic conditions viz. pH and proportion of the buffer and wavelength of detection, for achieving good sensitivity (peak area) and specificity (number of theoretical plates). A desirability function was employed to identify the optimized conditions, which gave a highest value of 0.971. The optimized chromatographic conditions were: pH of the buffer: 4.7, wavelength of detection: 215 nm and proportion of buffer in mobile phase: 84.7% v/v for responses: 124839.6 mV ∗ min as the peak area (1 μg/mL) and 20,000 as the theoretical plate number for the same. A simple protein precipitation method, using methanol, was employed to extract RUFI from the biological matrices. Piribedil was used as the internal standard (IS). At the optimized conditions, the LOQ values of RUFI in plasma and brain were found to be 13.84 ng/mL and 105.24 ng/g respectively. The developed method was validated as per ICH guidelines and its applicability in analysing RUFI in rat plasma and brain matrices was demonstrated by i.v. administration in rats. The AUC0-t in plasma was found to be 91.9% of AUC0-∞ indicating that the method is very sensitive and can capture almost the entire plasma time course of RUFI, at a dose of 0.5 mg/kg.