Investigation and Prediction of Tensile, Flexural, and Compressive Properties of Tough PLA Material Using Definitive Screening Design

The material extrusion fused deposition modeling (FDM) technique has become a widely used technique that enables the production of complex parts for various applications. To overcome limitations of PLA material such as low impact toughness, commercially available materials such as UltiMaker Tough PLA were produced to improve the parent PLA material that can be widely applied in many engineering applications. In this study, 3D-printed parts (test specimens) considering six different printing parameters (i.e., layer height, wall thickness, infill density, build plate temperature, printing speed, and printing temperature) are experimentally investigated to understand their impact on the mechanical properties of Tough PLA material. Three different standardized tests of tensile, flexural, and compressive properties were conducted to determine the maximum force and Young's modulus. These six properties were used as responses in a design of experiment, definitive screening design (DSD), to build six regression models. Analysis of variance (ANOVA) is performed to evaluate the effects of each of the six printing parameters on Tough PLA mechanical properties. It is shown that all regression models are statistically significant (p<0.05) with high values of adjusted and predicted R2. Conducted confirmation tests resulted in low relative errors between experimental and predicted data, indicating that the developed models are adequately accurate and reliable for the prediction of tensile, flexural, and compressive properties of Tough PLA material.

Analyzing Surface Roughness Variations in Material Extrusion Additive Manufacturing of Nylon Carbon Fiber Composites

In recent years, fused deposition modeling (FDM) based on material extrusion additive manufacturing technology has become widely accepted as a cost-effective method for fabricating engineering components with net-shapes. However, the limited exploration of the influence of FDM process parameters on surface roughness parameters, i.e., Ra (average surface roughness), Rq (root mean square surface roughness), and Rz (maximum height of the profile) across different sides (bottom, top, and walls) poses a challenge for the fabrication of functional parts. This research aims to bridge the knowledge gap by analyzing surface roughness under various process parameters and optimizing it for nylon carbon fiber printed parts. A definitive screening design (DSD) was employed for experimental runs. The Pareto chart highlighted the significant effects of layer height, part orientation, and infill density on all surface roughness parameters and respective sides. The surface morphology was analyzed through optical microscopy. Multi-response optimization was performed using an integrated approach of composited desirability function and entropy. The findings of the present study hold significant industrial applications, enhancing the quality and performance of 3D printed parts. From intricate prototypes to durable automotive components, the optimized surfaces contribute to production of functional and visually appealing products across various sectors.

Optimizing the Functional Properties of Starch-Based Biodegradable Films

A definitive screening design was used in order to evaluate the effects of starch, glycerol and montmorillonite (MMT) concentrations, as well as the drying temperature, drying tray type and starch species, on packaging film's functional properties. Optimization showed that in order to obtain films with the minimum possible thickness, the maximum elongation at break, the maximum tensile strength, as well as reduced water vapor permeability and low opacity, a combination of factors should be used as follows: 5.5% wt starch concentration, 30% wt glycerol concentration on a dry starch basis, 10.5% wt MMT concentration on a dry starch basis, 45 °C drying temperature, chickpea as the starch species and plexiglass as the drying tray type. Based on these results, starch films were prepared, and fresh minced meat was stored in them for 3 days. It was shown that the incorporation of MMT at 10.5% wt on a dry starch basis in the packaging films led to a decreased mesophilic and psychrotrophic bacteria growth factor compared to commercial packaging. When assessed for their biodegradability, the starch films disintegrated after 10 days of thermophilic incubation under simulated composting conditions. Finally, to prove their handling capability during industrial production, the starch films were rewound in a paper cylinder using an industrial-scale rewinding machine.

Application of definitive screening design to optimization of the protein extraction and functional properties of proteins in Auricularia auricula

BACKGROUND

Auricularia auricula (A. auricula) is one of the most abundant sources of plant protein in edible fungi. Problems of low protein yield exist in traditional methods of protein extraction such as alkali extraction and ultrasonic-assisted alkali after pretreatment with enzymes. Thus, the protein extraction process was investigated and optimized using a definitive screening design from A. auricula to improve the protein yield under practical operating conditions of temperature, the concentration of NaCl, meal/water ratio, extraction time and pH.

RESULTS

The yield of protein isolates of the isoelectric-ammonium sulfate precipitation (9.34% w/w) was obtained almost three times and the protein content (55.23% w/w) was approximately 1.6 times that of the traditional extraction method of isoelectric precipitation. Next, the optimized method was successfully applied to the analysis of the functional properties of the protein. A. auricula protein isolate (AAPI) had better solubility, emulsification and foaming capacity than soy protein isolate (SPI) and pea protein isolate (PPI), and the oil holding capacity of AAPI exhibited extremely well, which was approximately five times that of SPI and six times that of PPI. The texture properties of AAPI gel were similar to those of PPI gels.

CONCLUSION

AAPI extracted by the optimized method had a satisfactory yield and had the potential to substitute plant-originated proteins in food processing. © 2022 Society of Chemical Industry.

Parametric Investigation and Optimization to Study the Effect of Process Parameters on the Dimensional Deviation of Fused Deposition Modeling of 3D Printed Parts

Fused deposition modeling (FDM) is the most economical additive manufacturing (AM) technology available for fabricating complex part geometries. However, the involvement of numerous control process parameters and dimensional instabilities are challenges of FDM. Therefore, this study investigated the effect of 3D printing parameters on dimensional deviations, including the length, width, height, and angle of polylactic acid (PLA) printed parts. The selected printing parameters include layer height, number of perimeters, infill density, infill angle, print speed, nozzle temperature, bed temperature, and print orientation. Three-level definitive screening design (DSD) was used to plan experimental runs. The results revealed that infill density is the most consequential parameter for length and width deviation, while layer height is significant for angle and height deviation. The regression models developed for the four responses are non-linear quadratic. The optimal results are obtained considering the integrated approach of desirability and weighted aggregated sum product assessment (WASPAS). The optimal results include a layer height of 0.1 mm, a total of six perimeters, an infill density of 20%, a fill angle of 90°, a print speed of 70 mm/s, a nozzle temperature of 220 °C, a bed temperature of 70 °C, and a print orientation of 90°. The current study provides a guideline to fabricate assistive devices, such as hand and foot orthoses, that require high dimensional accuracies.

Optimization of Heavy Metals Biosorption via Artificial Neural Network: A Case Study of Cobalt (II) Sorption by Pseudomonas alcaliphila NEWG-2

The definitive screening design (DSD) and artificial neural network (ANN) were conducted for modeling the biosorption of Co(II) by Pseudomonas alcaliphila NEWG-2. Factors such as peptone, incubation time, pH, glycerol, glucose, K2HPO4, and initial cobalt had a significant effect on the biosorption process. MgSO4 was the only insignificant factor. The DSD model was invalid and could not forecast the prediction of Co(II) removal, owing to the significant lack-of-fit (P < 0.0001). Decisively, the prediction ability of ANN was accurate with a prominent response for training (R2 = 0.9779) and validation (R2 = 0.9773) and lower errors. Applying the optimal levels of the tested variables obtained by the ANN model led to 96.32 ± 2.1% of cobalt bioremoval. During the biosorption process, Fourier transform infrared spectroscopy (FTIR), energy-dispersive X-ray spectroscopy, and scanning electron microscopy confirmed the sorption of Co(II) ions by P. alcaliphila. FTIR indicated the appearance of a new stretching vibration band formed with Co(II) ions at wavenumbers of 562, 530, and 531 cm-1. The symmetric amino (NH2) binding was also formed due to Co(II) sorption. Interestingly, throughout the revision of publications so far, no attempt has been conducted to optimize the biosorption of Co(II) by P. alcaliphila via DSD or ANN paradigm.

Optimization of Lipid Nanoparticles for saRNA Expression and Cellular Activation Using a Design-of-Experiment Approach

Lipid nanoparticles (LNPs) are the leading technology for RNA delivery, given the success of the Pfizer/BioNTech and Moderna COVID-19 mRNA (mRNA) vaccines, and small interfering RNA (siRNA) therapies (patisiran). However, optimization of LNP process parameters and compositions for larger RNA payloads such as self-amplifying RNA (saRNA), which can have complex secondary structures, have not been carried out. Furthermore, the interactions between process parameters, critical quality attributes (CQAs), and function, such as protein expression and cellular activation, are not well understood. Here, we used two iterations of design of experiments (DoE) (definitive screening design and Box-Behnken design) to optimize saRNA formulations using the leading, FDA-approved ionizable lipids (MC3, ALC-0315, and SM-102). We observed that PEG is required to preserve the CQAs and that saRNA is more challenging to encapsulate and preserve than mRNA. We identified three formulations to minimize cellular activation, maximize cellular activation, or meet a CQA profile while maximizing protein expression. The significant parameters and design of the response surface modeling and multiple response optimization may be useful for designing formulations for a range of applications, such as vaccines or protein replacement therapies, for larger RNA cargoes.

Rational Design of CRISPR/Cas12a-RPA Based One-Pot COVID-19 Detection with Design of Experiments

Simple and effective molecular diagnostic methods have gained importance due to the devastating effects of the COVID-19 pandemic. Various isothermal one-pot COVID-19 detection methods have been proposed as favorable alternatives to standard RT-qPCR methods as they do not require sophisticated and/or expensive devices. However, as one-pot reactions are highly complex with a large number of variables, determining the optimum conditions to maximize sensitivity while minimizing diagnostic cost can be cumbersome. Here, statistical design of experiments (DoE) was employed to accelerate the development and optimization of a CRISPR/Cas12a-RPA-based one-pot detection method for the first time. Using a definitive screening design, factors with a significant effect on performance were elucidated and optimized, facilitating the detection of two copies/μL of full-length SARS-CoV-2 (COVID-19) genome using simple instrumentation. The screening revealed that the addition of a reverse transcription buffer and an RNase inhibitor, components generally omitted in one-pot reactions, improved performance significantly, and optimization of reverse transcription had a critical impact on the method’s sensitivity. This strategic method was also applied in a second approach involving a DNA sequence of the N gene from the COVID-19 genome. The slight differences in optimal conditions for the methods using RNA and DNA templates highlight the importance of reaction-specific optimization in ensuring robust and efficient diagnostic performance. The proposed detection method is automation-compatible, rendering it suitable for high-throughput testing. This study demonstrated the benefits of DoE for the optimization of complex one-pot molecular diagnostics methods to increase detection sensitivity.

Definitive screening accelerates Taxol biosynthetic pathway optimization and scale up in Saccharomyces cerevisiae cell factories

BACKGROUND

Recent technological advancements in synthetic and systems biology have enabled the construction of microbial cell factories expressing diverse heterologous pathways in unprecedentedly short time scales. However, the translation of such laboratory scale breakthroughs to industrial bioprocesses remains a major bottleneck.

METHODS AND MAJOR RESULTS

In this study, an accelerated bioprocess development approach was employed to optimize the biosynthetic pathway of the blockbuster chemotherapy drug, Taxol. Statistical design of experiments approaches were coupled with an industrially relevant high-throughput microbioreactor system to optimize production of key Taxol intermediates, Taxadien-5α-ol and Taxadien-5α-yl-acetate, in engineered yeast cell factories. The optimal factor combination was determined via data driven statistical modelling and validated in 1 L bioreactors leading to a 2.1-fold improvement in taxane production compared to a typical defined media. Elucidation and mitigation of nutrient limitation enhanced product titers a further two-fold and titers of the critical Taxol precursors, Taxadien-5α-ol and Taxadien-5α-yl-acetate were improved to 34 and 11 mg L^-1 , representing a three-fold improvement compared to the highest literature titers in S. cerevisiae. Comparable titers were obtained when the process was scaled up a further five-fold using 5 L bioreactors.

CONCLUSIONS

The results of this study highlight the benefits of a holistic design of experiments guided approach to expedite early stage bioprocess development.

Effects of Manufacturing Process Variables on the Tablet Weight Variation of Mini-tablets Clarified by a Definitive Screening Design

This study investigated the effect of manufacturing process variables of mini-tablets, in particular, the effect of process variables concerning fluidized bed granulation on tablet weight variation. Test granules were produced with different granulation conditions according to a definitive screening design (DSD). The five evaluated factors assigned to DSD were: the grinding speed of the sample mill at the grinding process of the active pharmaceutical ingredient (X1), microcrystalline cellulose content in granules (X2), inlet air temperature (X3), binder concentration (X4) and the spray speed of the binder solution (X5) at the granulation process. First, the relationships between the evaluated factors and the granule properties were investigated. As a result of the DSD analysis, the mode of action of granulation parameters on the granule properties was fully characterized. Subsequently, the variation in tablet weight was examined. In addition to mini-tablets (3 mm diameter), this experiment assessed regular tablets (8 mm diameter). From the results for regular tablets, the variation in tablet weight was affected by the flowability of granules. By contrast, regarding the mini-tablets, no significant effect on the variation of tablet weight was found from the evaluated factors. From this result, this study further focused on other important factors besides the granulation process, and then the effect of the die-hole position of the multiple-tip tooling on tablet weight variation was proven to be significant. Our findings provide a better understanding of manufacturing mini-tablets.

[Definitive screening design combined with design space for optimizing purification process of Scutellariae Radix extract]

In the pharmacopoeia, many process parameters for the purification process of Scutellariae Radix are unclear. In this study, deterministic screening design combined with design space method was used to optimize the purification process of Scutellariae Radix extract. Nine method parameters such as mass fraction of solution(X_1), first acid precipitation pH(X_2) and first holding time(X_3) in the purification process were firstly studied by definitive screening design. The yield of baicalin was defined as the evaluation index. A stepwise regression method was used then to build quantitative models between evaluation index and method parameters and the three most critical impact parameters were determined. Probability-based design space was calculated and successfully verified with the experimental error simulation method. Finally, the second standing temperature, the first standing temperature and the pH value of the second acid precipitation were determined as the three most critical method parameters. The recommended operating space was as follows: the second standing temperature 5-7 ℃, the first standing temperature 13-15 ℃, and the pH of the second acid precipitation 1.5-1.7. Within this operating space, the baicalin yield in the purification process was over 80%, and the probability of reaching the standard was over 0.96. In this study, we optimized the effect of various parameters for the purification process of the Scutellariae Radix extract in the pharmacopoeia on the yield of baicalin and provided a reference for industrial production of the exact of Scutellariae Radix.

Rapid serum-free/suspension adaptation: Medium development using a definitive screening design for Chinese hamster ovary cells

The biopharmaceutical industry prefers to culture the mammalian cells in suspension with a serum-free media (SFM) due to improved productivity and process consistency. However, mammalian cells preferentially grow as adherent cells in a complete medium (CM) containing serum. Therefore, cells require adaptation from adherence in CM to suspension culture in SFM. This work proposes an adaptation method that includes media supplementation during the adaption of Chinese hamster ovary cells. As a result, the adaptation was accelerated compared to the traditional repetitive subculturing. Ca²⁺ /Mg²⁺ supplementation significantly reduced the doubling time compared to the adaptation without supplementation during the adaptation of adherent cells from 100% CM to 75% CM (p < 0.05). Furthermore, a definitive screening design (DSD) was applied to select essential nutrients during the adaptation from 10% CM to 0% CM. The main effects of Ca²⁺ and Dulbecco's modified essential medium (DMEM) were found significant to both viable cell density and viability at harvest. Additionally, the interaction term between Ca²⁺ and DMEM was found significant, which highlights the ability of DSD to capture interaction terms. Eventually, the media supplementation method resulted in adaptation SFM in 27 days, compared to the previously reported 66 days. Additionally, the membrane surface integrin expression was found significantly decreased when adherent cells were adapted to suspension. Moreover, the Ca²⁺ /Mg²⁺ supplementation correlated with faster integrin recovery after trypsinization. However, faster integrin recovery did not contribute to the accelerated cell growth when subculturing from 100% CM to 75% CM.

Process Characterization by Definitive Screening Design Approach on DNA Vaccine Production

Plasmid DNA is a vital biological tool for molecular cloning and transgene expression of recombinant proteins; however, decades ago, it has become an exceptionally appealing as a potential biopharmaceutical product as genetic immunization for animal and human use. The demand for large-quantity production of DNA vaccines also increases. Thus, we, herein, presented a systematic approach for process characterization of fed-batch Escherichia coli DH5α fermentation producing a porcine DNA vaccine. Design of Experiments (DoE) was employed to determine process parameters that have impacts on a critical quality attribute of the product, which is the active form of plasmid DNA referred as supercoiled plasmid DNA content, as well as the performance attributes, which are volumetric yield and specific yield from fermentation. The parameters of interest were temperature, pH, dissolved oxygen, cultivation time, and feed rate. Using the definitive-screening design, there were 16 runs, including 3 additional center points to create the predictive model, which then was used to simulate the operational ranges for capability analysis.

Development of High-Performance Whole Cell Biosensors Aided by Statistical Modeling

Whole cell biosensors are genetic systems that link the presence of a chemical, or other stimulus, to a user-defined gene expression output for applications in sensing and control. However, the gene expression level of biosensor regulatory components required for optimal performance is nonintuitive, and classical iterative approaches do not efficiently explore multidimensional experimental space. To overcome these challenges, we used a design of experiments (DoE) methodology to efficiently map gene expression levels and provide biosensors with enhanced performance. This methodology was applied to two biosensors that respond to catabolic breakdown products of lignin biomass, protocatechuic acid and ferulic acid. Utilizing DoE we systematically modified biosensor dose-response behavior by increasing the maximum signal output (up to 30-fold increase), improving dynamic range (>500-fold), expanding the sensing range (∼4-orders of magnitude), increasing sensitivity (by >1500-fold), and modulated the slope of the curve to afford biosensors designs with both digital and analogue dose-response behavior. This DoE method shows promise for the optimization of regulatory systems and metabolic pathways constructed from novel, poorly characterized parts.

[Quantitative chromatographic fingerprint analysis of Sanye Tangzhiqing Decoction based on quality by design concept]

In this work,a high performance liquid chromatography-ultraviolet( HPLC-UV) detection technology was used to establish fingerprint analysis method for Sanye Tangzhiqing Decoction following an analytical quality by design( AQb D) approach. Firstly,column temperature,flow rate,and gradient elution conditions were determined as the method parameters needing to be optimized. Then according to the results of definitive screening design,three critical method attributes( CMAs) were identified,including peak number,the percentage of common peak area to total peak area,and retention time of the last peak. A stepwise regression method was used then to build quantitative models between CMAs and method parameters. Probability-based design space was calculated and successfully verified using the experimental error simulation method. After the analysis conditions were optimized,the contents of six components,namely chlorogenic acid,paeoniflorin,rutin,hyperoside,quercetin-3-O-β-D-glucuronide,and salvianolic acid B were simultaneously determined. There were 19 common peaks in the fingerprint and their common peak area accounted for 96% of the total peak area. Both fingerprint and quantitative analysis methods were validated applicable in methodology study,and they can be applied to determine new samples.

The Usefulness of Definitive Screening Design for a Quality by Design Approach as Demonstrated by a Pharmaceutical Study of Orally Disintegrating Tablet

Definitive screening design (DSD) is a new class of small three-level experimental design that is attracting much attention as a technical tool of a quality by design (QbD) approach. The purpose of this study is to examine the usefulness of DSD for QbD through a pharmaceutical study on the preparation of ethenzamide-containing orally disintegrating tablet. Model tablets were prepared by directly compressing the mixture of the active pharmaceutical ingredient (API) and excipients. The five evaluated factors assigned to DSD were: the contents of API (X1) and lubricant (X2), and the compression force (X3) of the tableting process, the mixing time (X4), and the filling ratio of powder in the V-type mixer (X5). After tablet preparation, hardness and disintegration time were measured. The same experiments were performed by using the conventional design of experiments [i.e., L8 and L16 orthogonal array designs and central composite design (CCD)]. Results showed that DSD successfully clarified how various factors contribute to tablet properties. Moreover, the analysis result from DSD agreed well with those from the L8 and L16 experiments. In additional experiments, response surfaces for tablet properties were created by DSD. Compared with the response surfaces created by CCD, DSD could produce reliable response surfaces for its smaller number of experiments. We conclude that DSD is a powerful tool for implementing pharmaceutical studies including the QbD approach.

Development and Qualification of a Scale-Down Mammalian Cell Culture Model and Application in Design Space Development by Definitive Screening Design

Scale-down models are indispensable and crucial tools for process understanding and continuous process improvement in product life-cycle management. In this study, a scale-down model representing commercial-scale cell culture process of adalimumab biosimilar HS016 was first developed based on constant power per volume (P/V) principle and then qualified by multivariate data analysis (MVDA) and equivalence test method. The trajectories of the bench-scale process lie in the middle of the control range of large-scale process, built by multivariate evolution model based on nutrients, metabolites, and process performance datasets. This indicates that the small-scale process performance is comparable with that of the full-scale process. The final product titer, integrated viable cell density (iVCD), viability, aggregates, acid peak content, total afucosylation level, and high mannose content recognized as key process attributes (KPAs) or critical quality attributes (CQAs) were equivalent across the scales upon comparison using equivalence test method. The qualified scale-down model was then used for process characterization using a definitive screening design (DSD) where five independent variables including pH, shifted temperature, inoculation seeding density, viable cell density (VCD) at first feeding, VCD at temperature shift were evaluated. Three quadratic polynomial models for final product titer, aggregation, and high mannose were then established using the DSD results. The design space was finally developed using a probability-based Monte Carlo simulation method and was verified with the operation setpoint and worst-case condition. The case study presented in this report shows a feasible roadmap for cell culture process characterization.

Seasonal Variations in the Metabolome and Bioactivity Profile of Fucus vesiculosus Extracted by an Optimised, Pressurised Liquid Extraction Protocol

The metabolism of seaweeds depends on environmental parameters, the availability of nutrients, and biotic/abiotic stresses; therefore, their chemical composition fluctuates throughout the year. This study investigated seasonal variations in the metabolome of the Baltic Sea brown alga Fucus vesiculosus and its potential relation to the bioactivity profile. By using a definitive screening design (DSD) combined with pressurised liquid extraction (PLE), an optimised protocol was developed to extract algal biomass monthly for a full calendar year. An untargeted metabolomics approach using ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MSn)-based molecular networking and manual dereplication was employed. The extracts were simultaneously screened for their in vitro antimicrobial, anticancer/apoptotic, and free radical scavenging activities. 44 compounds were putatively dereplicated in the metabolome. Many compounds were found to vary with the sampling month; phlorotannin total ion count (TIC) was highest in summer, whilst chlorophylls, lipids, and carotenoids peaked in winter and spring. The greatest radical scavenging and apoptotic activities against pancreas cancer cells observed in the summer months were attributed to high phlorotannin TIC. Methicillin-resistant Staphylococcus aureus (MRSA) inhibitory activity was produced year-round without a clear seasonal trend. This is the first study applying DSD-based optimised PLE extraction combined with a metabolome analysis of F. vesiculosus for the identification of seasonal variations in both metabolome and bioactivity.