Bioprocess optimization using design-of-experiments methodology

Application of quality by design in optimization of nanoformulations: Principle, perspectives and practices

Nanoparticulate drug delivery systems (NDDS) based nanoformulations have emerged as promising drug delivery systems. Various NDDS-based formulations have been reported such as polymeric nanoparticles (NPs), nanoliposomes, solid lipid NPs, nanocapsules, liposomes, self-nano emulsifying drug delivery systems, pro liposomes, nanospheres, microemulsion, nanoemulsion, gold NPs, silver NPs and nanostructured lipid carrier. They have shown numerous advantages such as enhanced bioavailability, aqueous solubility, permeability, controlled release profile, and blood-brain barrier (BBB) permeability. This advantage of NDDS can help to deliver pure drugs to the target site. However, the formulation of nanoparticles is a complex process that requires optimization to ensure product quality and efficacy. Quality by Design (QbD) is a systemic approach that has been implemented in the pharmaceutical industry to improve the quality and reliability of drug products. QbD involves the optimization of different parameters like zeta potential (ZP), particle size (PS), entrapment efficiency (EE), polydispersity index (PDI), and drug release using statistical experimental design. The present article discussed the detailed role of QbD in optimizing nanoformulations and their advantages, advancement, and applications from the industrial perspective. Various case studies of QbD in the optimization of nanoformulations are also discussed.

Influence of multi-stressor combinations of pCO2, temperature, and salinity on the toxicity of Heterosigma akashiwo (Raphidophyceae), a fish-killing flagellate

Climate change and global warming have led to more frequent harmful algal blooms in the last decade. Among these blooms, Heterosigma akashiwo, a golden-brown phytoflagellate, is one of the 40 species with a high potential to form harmful blooms, leading to significant fish mortality. Climate change leads to rising atmospheric and ocean temperatures. These changes, along with altered rainfall patterns and meltwater input, can cause fluctuations in ocean salinity. Elevated atmospheric carbon dioxide (CO2) levels increase water acidity as oceans absorb CO2. This study investigated the effects of temperature, salinity, and CO2 levels on lipid production, hemolytic activity, and toxicity of H. akashiwo using the design of experiment approach, which can be used to investigate the effect of two or more factors on the same response simultaneously in a precise manner with fewer experiments and materials but in a larger region of the factor space. The lipid content was measured using a high-throughput Nile Red method, and the highest level of lipid content was detected at 25°C, a salinity of 30, and a CO2 concentration of 400 ppm. Hemolytic activity was assessed using rabbit blood erythrocytes in a 96-well plate, and the optimal conditions for achieving the highest hemolytic activity were determined at 15°C, a salinity of 10, and a CO2 concentration of 400 ppm. As the chemical structure of the toxin is not known, we used the toxicity against the cell line RTgill-W1 as the cell toxicity proxy. The maximum toxicity was identified at 15°C, a salinity of 10, and a CO2 level of 700 ppm.

Poly-γ-glutamic acid overproduction of Bacillus licheniformis ATCC 9945a by developing a novel optimum culture medium and glutamate pulse feeding using different experimental design approaches

The commercial production of multifunctional, biocompatible, and biodegradable biopolymers such as poly-γ-glutamic acid via microbial fermentation requires the development of simple and cheap methods for mass production. This study optimized the poly-γ-glutamic acid production of Bacillus licheniformis ATCC 9945a in several steps. At first, the most critical components of the culture medium, including l-glutamic acid, citric acid, and glycerol, were selected by screening nine factors through the Plackett-Burman experimental design and then were optimized using the response surface method and the central composite design algorithm. Under optimal conditions, the production of poly-γ-glutamic acid increased by more than 4.2 times from 11.2 to 47.2 g/L. This is one of the highest production rates of this strain in submerged batch fermentation reported so far using the optimized medium compared to the conventional base medium. A novel and efficient sudden pulse feeding strategy (achieved by a novel one-factorial statistical technique) of l-glutamic acid to the optimized medium increased biopolymer production from 47.2 to 66.1 g/L, the highest value reported in published literature with this strain. This simple, reproducible, and cheap fermentation process can considerably enhance the commercial applications of the poly-γ-glutamic acid synthesized by B. licheniformis ATCC 9945a.

Implementation of mDoE-methods to a microcarrier-based expansion processes for mesenchymal stem cells

The need for advanced therapy medicinal products (ATMPs) has gained increased attention in recent years. In this respect, a well-designed cell expansion process is needed to efficiently manufacture the required number of cells with the desired product quality. This step is challenging due to the biological complexity of the respective primary cell (e.g., mesenchymal stem cells (MSC)) and the usage of microcarrier-based expansion systems. One accelerating approach for process design is model-assisted Design of Experiments (mDoE) combining mathematical process models and statistical tools. In this study, the mDoE workflow was used for the development of an expansion processes with human immortalized mesenchymal stem cells (hMSC-TERT) and the aim of maximizing cell yield assuming only a limited amount of prior knowledge at a very early stage of development. First, suitable microcarriers for expansion in shake flasks were screened and the differentiation of the cells was proven. Second, initial experiments were performed to generate prior knowledge, which was then used to set up the mathematical model and to estimate the model parameters. Finally, the mDoE was used to determine and evaluate the design space to be performed experimentally. Overall, a cell expansion process using microcarriers in a shake flask culture was successfully implemented and a significant increase in cell yield (up to 6,2-fold) was achieved compared to literature.

Bayesian cell therapy process optimization

Optimizing complex bioprocesses poses a significant challenge in several fields, particularly in cell therapy manufacturing. The development of customized, closed, and automated processes is crucial for their industrial translation and for addressing large patient populations at a sustainable price. Limited understanding of the underlying biological mechanisms, coupled with highly resource-intensive experimentation, are two contributing factors that make the development of these next-generation processes challenging. Bayesian optimization (BO) is an iterative experimental design methodology that addresses these challenges, but has not been extensively tested in situations that require parallel experimentation with significant experimental variability. In this study, we present an evaluation of noisy, parallel BO for increasing noise levels and parallel batch sizes on two in silico bioprocesses, and compare it to the industry state-of-the-art. As an in vitro showcase, we apply the method to the optimization of a monocyte purification unit operation. The in silico results show that BO significantly outperforms the state-of-the-art, requiring approximately 50% fewer experiments on average. This study highlights the potential of noisy, parallel BO as valuable tool for cell therapy process development and optimization.

"High-throughput screening of catalytically active inclusion bodies using laboratory automation and Bayesian optimization"

BACKGROUND

In recent years, the production of inclusion bodies that retain substantial catalytic activity was demonstrated. These catalytically active inclusion bodies (CatIBs) are formed by genetic fusion of an aggregation-inducing tag to a gene of interest via short linker polypeptides. The resulting CatIBs are known for their easy and cost-efficient production, recyclability as well as their improved stability. Recent studies have outlined the cooperative effects of linker and aggregation-inducing tag on CatIB activities. However, no a priori prediction is possible so far to indicate the best combination thereof. Consequently, extensive screening is required to find the best performing CatIB variant.

RESULTS

In this work, a semi-automated cloning workflow was implemented and used for fast generation of 63 CatIB variants with glucose dehydrogenase of Bacillus subtilis (BsGDH). Furthermore, the variant BsGDH-PT-CBDCell was used to develop, optimize and validate an automated CatIB screening workflow, enhancing the analysis of many CatIB candidates in parallel. Compared to previous studies with CatIBs, important optimization steps include the exclusion of plate position effects in the BioLector by changing the cultivation temperature. For the overall workflow including strain construction, the manual workload could be reduced from 59 to 7 h for 48 variants (88%). After demonstration of high reproducibility with 1.9% relative standard deviation across 42 biological replicates, the workflow was performed in combination with a Bayesian process model and Thompson sampling. While the process model is crucial to derive key performance indicators of CatIBs, Thompson sampling serves as a strategy to balance exploitation and exploration in screening procedures. Our methodology allowed analysis of 63 BsGDH-CatIB variants within only three batch experiments. Because of the high likelihood of TDoT-PT-BsGDH being the best CatIB performer, it was selected in 50 biological replicates during the three screening rounds, much more than other, low-performing variants.

CONCLUSIONS

At the current state of knowledge, every new enzyme requires screening for different linker/aggregation-inducing tag combinations. For this purpose, the presented CatIB toolbox facilitates fast and simplified construction and screening procedures. The methodology thus assists in finding the best CatIB producer from large libraries in short time, rendering possible automated Design-Build-Test-Learn cycles to generate structure/function learnings.

Optimization of adaptation parameters from adhesion cell culture in serum-containing media to suspension in chemically defined media by superlative box design

A new design of experiments-superlative box design (SBD), was adopted to optimize the adaptation of Chinese hamster ovary cells from adhesion culture to serum-free suspension culture. It is a general trend to use a serum-free medium instead of a serum-containing medium. The advantage of serum-free medium (chemically defended) is that it does not contain unknown components and avoids safety issues. SBD requires fewer experiments while ensuring a sufficient number of experiments and uniformity in the distribution of experiments amongst all the factors. Six factors were considered in this experimental design with 43 runs plus three more repeating center runs. The cell line was adapted to serum-free media by gradually reducing serum, and from adherent to suspension by rotating at various speeds in a shake flask. Response surface methodology was applied to find the optimum condition. The optimized cell density reached 7.02 × 105 cells/mL, calculated by the quadratic model. Experiments validated the predicted cell adaptation with the maximum cell density. Three suspension runs were selected randomly to perform in the bioreactor to validate cell stability and production homogeneity. This study provides an efficient method to transfer adherent cells to suspension cells and is the first to successfully use SBD and establish a parameter quadratic optimization model.

Pushing the boundaries of phosphorylase cascade reaction for cellobiose production I: Kinetic model development

One-pot cascade reactions of coupled disaccharide phosphorylases enable an efficient transglycosylation via intermediary α-d-glucose 1-phosphate (G1P). Such transformations have promising applications in the production of carbohydrate commodities, including the disaccharide cellobiose for food and feed use. Several studies have shown sucrose and cellobiose phosphorylase for cellobiose synthesis from sucrose, but the boundaries on transformation efficiency that result from kinetic and thermodynamic characteristics of the individual enzyme reactions are not known. Here, we assessed in a step-by-step systematic fashion the practical requirements of a kinetic model to describe cellobiose production at industrially relevant substrate concentrations of up to 600 mM sucrose and glucose each. Mechanistic initial-rate models of the two-substrate reactions of sucrose phosphorylase (sucrose + phosphate → G1P + fructose) and cellobiose phosphorylase (G1P + glucose → cellobiose + phosphate) were needed and additionally required expansion by terms of glucose inhibition, in particular a distinctive two-site glucose substrate inhibition of the cellobiose phosphorylase (from Cellulumonas uda). Combined with mass action terms accounting for the approach to equilibrium, the kinetic model gave an excellent fit and a robust prediction of the full reaction time courses for a wide range of enzyme activities as well as substrate concentrations, including the variable substoichiometric concentration of phosphate. The model thus provides the essential engineering tool to disentangle the highly interrelated factors of conversion efficiency in the coupled enzyme reaction; and it establishes the necessary basis of window of operation calculations for targeted optimizations toward different process tasks.

Bioprocessing of Epothilone B from Aspergillus fumigatus under solid state fermentation: Antiproliferative activity, tubulin polymerization and cell cycle analysis

Epothilone derivatives have been recognized as one of the most powerful anticancer drugs towards solid tumors, for their unique affinity to bind with β-tubulin microtubule arrays, stabilizing their disassembly, causing cell death. Sornagium cellulosum is the main source for Epothilone, however, the fermentation bioprocessing of this myxobacteria is the main challenge for commercial production of Epothilone. The metabolic biosynthetic potency of epothilone by Aspergillus fumigatus, an endophyte of Catharanthus roseus, raises the hope for commercial epothilone production, for their fast growth rate and feasibility of manipulating their secondary metabolites. Thus, nutritional optimization of A. fumigatus for maximizing their epothilone productivity under solid state fermentation process is the objective. The highest yield of epothilone was obtained by growing A. fumigatus on orange peels under solid state fermentation (2.2 μg/g), bioprocessed by the Plackett-Burman design. The chemical structure of the extracted epothilone was resolved from the HPLC and LC-MS/MS analysis, with molecular mass 507.2 m/z and identical molecular fragmentation pattern of epothilone B of S. cellulosum. The purified A. fumigatus epothilone had a significant activity towards HepG2 (IC50 0.98 μg/ml), Pancl (IC50 1.5 μg/ml), MCF7 (IC50 3.7 μg/ml) and WI38 (IC50 4.6 μg/ml), as well as a strong anti-tubulin polymerization activity (IC50 0.52 μg/ml) compared to Paclitaxel (2.0 μg/ml). The effect of A. fumigatus epothilone on the immigration ability of HepG2 cells was assessed, as revealed from the wound closure of the monolayer cells that was estimated by ~ 63.7 and 72.5%, in response to the sample and doxorubicin, respectively, compared to negative control. From the Annexin V-PI flow cytometry results, a significant shift of the normal cells to the apoptosis was observed in response to A. fumigatus epothilone by ~ 20 folds compared to control cells, with the highest growth arrest of the HepG2 cells at the G0-G1 stage.

Bioconversion of waste glycerol into viscosinamide by Pseudomonas fluorescens DR54 and its activity evaluation

Lipopeptides, derived from microorganisms, are promising surface-active compounds known as biosurfactants. However, the high production costs of biosurfactants, associated with expensive culture media and purification processes, limit widespread industrial application. To enhance the sustainability of biosurfactant production, researchers have explored cost-effective substrates. In this study, crude glycerol was evaluated as a promising and economical carbon source in viscosinamide production by Pseudomonas fluorescens DR54. Optimization studies using the Box - Behnken design and response surface methodology were performed. Optimal conditions for viscosinamide production including glycerol 70.8 g/L, leucine 2.7 g/L, phosphate 3.7 g/L, and urea 9.3 g/L were identified. Yield of viscosinamide production, performed under optimal conditions, reached 7.18 ± 0.17 g/L. Preliminary characterization of viscosinamide involved the measurement of surface tension. The critical micelle concentration of lipopeptide was determined to be 5 mg/L. Furthermore, the interactions between the viscosinamide and lipase from Candida rugosa (CRL) were investigated by evaluating the impact of viscosinamide on lipase activity and measuring circular dichroism. It was observed that the α-helicity of CRL increases with increasing viscosinamide concentration, while the random coil structure decreases.

Using design of experiments to guide genetic optimization of engineered metabolic pathways

Design of experiments (DoE) is a term used to describe the application of statistical approaches to interrogate the impact of many variables on the performance of a multivariate system. It is commonly used for process optimization in fields such as chemical engineering and material science. Recent advances in the ability to quantitatively control the expression of genes in biological systems open up the possibility to apply DoE for genetic optimization. In this review targeted to genetic and metabolic engineers, we introduce several approaches in DoE at a high level and describe instances wherein these were applied to interrogate or optimize engineered genetic systems. We discuss the challenges of applying DoE and propose strategies to mitigate these challenges.

ONE-SENTENCE SUMMARY

This is a review of literature related to applying Design of Experiments for genetic optimization.

Reusing wastewater from Coffea arabica processing to produce single-cell protein using Candida sorboxylosa: Optimizing of culture conditions

Coffee is a crop of significant socioeconomic importance, and the reuse of agri-food by-products and biowaste has great potential across several industries. Coffee wastewater (CWW) is a valuable resource containing essential nutrients that can be utilized by Candida sorboxylosa for single-cell protein (SCP) production. This utilization contributes to mitigating the negative impacts of agro-industrial waste. The optimization of culture conditions using the design of experiments (DoE) technique is crucial in understanding the environmental factors influencing metabolite production. In our study, the DoE technique was employed to analyze culture conditions, including room temperature, pH 8.4, agitation at 200 rpm, a headspace of 60% (v/v), and an inoculum of 0.75 DO600nm over 28-h period. This approach resulted in a remarkable SCP yield of 64.4% and dry cell weight (DCW) of 2.26 g/L. It is noteworthy that there is no literature reporting SCP production under alkaline pH conditions in yeast. Interestingly, our work demonstrated that an alkaline pH of 8.4 significantly influenced SCP production by C. sorboxylosa. The DoE technique proved to be an efficient statistical tool for optimizing culture conditions, offering several advantages, such as: (i) conducting cultures at room temperature to minimize unnecessary energy consumption; (ii) reducing the incubation time from 46 to 28 h, thereby enhancing overall productivity; (iii) achieving 1.7-fold increase in SCP yield compared to previous basal production levels.

High-throughput process development from gene cloning to protein production

In the post-genomic era, the demand for faster and more efficient protein production has increased, both in public laboratories and industry. In addition, with the expansion of protein sequences in databases, the range of possible enzymes of interest for a given application is also increasing. Faced with peer competition, budgetary, and time constraints, companies and laboratories must find ways to develop a robust manufacturing process for recombinant protein production. In this review, we explore high-throughput technologies for recombinant protein expression and present a holistic high-throughput process development strategy that spans from genes to proteins. We discuss the challenges that come with this task, the limitations of previous studies, and future research directions.

Hybrid modeling in bioprocess dynamics: Structural variabilities, implementation strategies, and practical challenges

Hybrid modeling, with an appropriate blend of the mechanistic and data-driven framework, is increasingly being adopted in bioprocess modeling, model-based experimental design (digital-twin), identification of critical process parameters, and optimization. However, the development of a hybrid model from experimental data is an inherently complex workflow, involving designed experiments, selection of the data-driven process, identification of model parameters, assessment fitness, and generalization capability. Depending on the complexity of the process system and purpose, each piece of these modules can flexibly be incorporated into the puzzle. However, this extra flexibility can be a cause of concern to trace an "optimal" model structure. In this paper, the development of hybrid models in a common bioprocess system, selection of data-driven components and their mapping to states, choice of parameter identification techniques, and model quality assurance are revisited. The challenges associated with hybrid-model development, and corrective actions have also been reviewed. The review also suggests the lack of data, and code sharing in communal repositories can be a hurdle in the exploration, and expansion of those tools in a bioprocess system.

Statistically-aided development of protein A affinity chromatography for enhancing recovery and controlling quality of a monoclonal antibody

Protein A chromatography is widely used for isolation of monoclonal antibodies (mAbs) from cell culture components. In this study, the effect of different process parameters of the Protein A purification namely, binding pH, elution pH, flow rate, neutralization pH and tween concentration, on the concentration and quality of the purified mAb were evaluated. Using design of experiments approach, the critical process parameters of protein A chromatography were identified and experimentally optimized. Their impact on quality attributes, such as size variants and charge variants, of the mAb was studied. Multivariate data analysis was subsequently performed using multiple linear regression and partial least squares regression methods. It was observed that the elution pH primarily governed the concentration of the purified mAb and the content of monomers and aggregates, while the tween concentration primarily influenced the main peak of the charge variants. This is the first study that evaluates the impact of tween concentration in buffers on the protein A chromatography purification step. These studies helped in identifying the design space and defining the target robust and optimal setpoints of the responses, which were subsequently verified experimentally. These setpoints not only passed the target criteria but also resulted in the highest recoveries during the investigation. Through this statistically-aided approach, an optimized and robust protein A chromatography process was rationally developed for purification of mAbs, while achieving the desired product quality. This study highlights the influence of multiple parameters of the protein A purification process on critical quality attributes of mAbs, such as the size and charge variants, which has been a very scarcely explored area.

Sustainable biosynthetic pathways to value-added bioproducts from hydroxycinnamic acids

The biorefinery concept, in which biomass is utilized for the production of fuels and chemicals, emerges as an eco-friendly, cost-effective, and renewable alternative to petrochemical-based production. The hydroxycinnamic acid fraction of lignocellulosic biomass represents an untapped source of aromatic molecules that can be converted to numerous high-value products with industrial applications, including in the flavor and fragrance sector and pharmaceuticals. This review describes several biochemical pathways useful in the development of a biorefinery concept based on the biocatalytic conversion of the hydroxycinnamic acids ferulic, caffeic, and p-coumaric acid into high-value molecules. KEY POINTS: • The phenylpropanoids bioconversion pathways in the context of biorefineries • Description of pathways from hydroxycinnamic acids to high-value compounds • Metabolic engineering and synthetic biology advance hydroxycinnamic acid-based biorefineries.

Enhanced Biomass Production of Recombinant Pfu DNA Polymerase Producer Escherichia coli BL21(DE3) by Optimization of Induction Variables Using Response Surface Methodology

Pfu DNA polymerase is one of the most preferred molecular enzymes that is isolated from the hyperthermophilic Pyrococcus furiosus and used for high-throughput DNA synthesis by the polymerase chain reaction. Therefore, an efficient Pfu DNA polymerase production method is necessary for molecular techniques. In the present study, Pfu DNA polymerase was expressed in recombinant Escherichia coli BL21(DE3) and significant parameters for the biomass production were optimized using the central composite design which is the most popular method of response surface methodology. Induction conditions including cell density prior induction (OD_600nm), post-induction temperature, IPTG concentration, and post-induction time and their interactions on biomass production were investigated. The maximum biomass production (14.1 g/L) in shake flasks was achieved using the following predicted optimal conditions: OD_600nm before induction of 0.4 and the induction at 32 °C for 7.7 h, with 0.6 mM IPTG. Optimized culture conditions were implemented to scale up experiments. 22% and 70% increase in biomass production was achieved in 3 L and 10 L bioreactors, respectively as compared to initial biomass production observed in unoptimized conditions. Similary, a 30% increase of Pfu DNA polymerase production was obtained after the optimization. The polymerase activity of the purifed Pfu DNA polymerase was assessed by PCR amplification and determined as 2.9 U/μl by comparison with commercial Pfu DNA polymerase. The findings of this study indicated that the proposed fermentation conditions will contribute to further scale‑up studies to enhance the biomass for the production of other recombinant proteins.

Current advances for omics-guided process optimization of microbial manufacturing

Currently, microbial manufacturing is widely used in various fields, such as food, medicine and energy, for its advantages of greenness and sustainable development. Process optimization is the committed step enabling the commercialization of microbial manufacturing products. However, the present optimization processes mainly rely on experience or trial-and-error method ignoring the intrinsic connection between cellular physiological requirement and production performance, so in many cases the productivity of microbial manufacturing could not been fully exploited at economically feasible cost. Recently, the rapid development of omics technologies facilitates the comprehensive analysis of microbial metabolism and fermentation performance from multi-levels of molecules, cells and microenvironment. The use of omics technologies makes the process optimization more explicit, boosting microbial manufacturing performance and bringing significant economic benefits and social value. In this paper, the traditional and omics technologies-guided process optimization of microbial manufacturing are systematically reviewed, and the future trend of process optimization is prospected.

Treatment of Pulp Black Liquor with an Ionic Liquid: Modeling and Optimization by Using Response Surface Methodology and Central Composite Design

In this study, selective extraction towards ionic liquid trihexyltetradecylphosphonium chloride ([P₆₆₆₁₄ ]Cl) of lignin residues, polysaccharides and organic acids present in black liquor (BL), the main principal wastewater of pulping industry was studied. With the objective of finding optimized conditions allowing to extract lignin residues while polysaccharides and organic acids remain in aqueous solution, a design of experiments approach based on a response surface methodology was used. Three continuous factors, namely initial pH varying from 9 to 13.5, dilution of BL varying from 5 to 20 and volumetric ratio of black liquor vs. ionic liquid R_V ., varying from 1 to 19, were investigated. Concentration of lignin residues, polysaccharides and organic acids were measured using Folin-Ciocalteu method, the anthrone method and HPLC, respectively. Results showed that a multi-response optimization led to the extraction of 84.8 % of lignin residues, 66.0 % of polysaccharides, and no extraction of OA under optimised conditions.

Rational search of genetic design space for a heterologous terpene metabolic pathway in Streptomyces

Modern tools in DNA synthesis and assembly give genetic engineers control over the nucleotide-level design of complex, multi-gene systems. Systematic approaches to explore genetic design space and optimize the performance of genetic constructs are lacking. Here we explore the application of a five-level Plackett-Burman fractional factorial design to improve the titer of a heterologous terpene biosynthetic pathway in Streptomyces. A library of 125 engineered gene clusters encoding the production of diterpenoid ent-atiserenoic acid (eAA) via the methylerythritol phosphate pathway was constructed and introduced into Streptomyces albidoflavus J1047 for heterologous expression. The eAA production titer varied within the library by over two orders of magnitude and host strains showed unexpected and reproducible colony morphology phenotypes. Analysis of Plackett-Burman design identified expression of dxs, the gene encoding the first and the flux-controlling enzyme, having the strongest impact on eAA titer, but with a counter-intuitive negative correlation between dxs expression and eAA production. Finally, simulation modeling was performed to determine how several plausible sources of experimental error/noise and non-linearity impact the utility of Plackett-Burman analyses.

Bayesian Optimization for an ATP-Regenerating In Vitro Enzyme Cascade

Enzyme cascades are an emerging synthetic tool for the synthesis of various molecules, combining the advantages of biocatalysis and of one-pot multi-step reactions. However, the more complex the enzyme cascade is, the more difficult it is to achieve adequate productivities and product concentrations. Therefore, the whole process must be optimized to account for synergistic effects. One way to deal with this challenge involves data-driven models in combination with experimental validation. Here, Bayesian optimization was applied to an ATP-producing and -regenerating enzyme cascade consisting of polyphosphate kinases. The enzyme and co-substrate concentrations were adjusted for an ATP-dependent reaction, catalyzed by mevalonate kinase (MVK). With a total of 16 experiments, we were able to iteratively optimize the initial concentrations of the components used in the one-pot synthesis to improve the specific activity of MVK with 10.2 U mg−1. The specific activity even exceeded the results of the reference reaction with stoichiometrically added ATP amounts, with which a specific activity of 8.8 U mg−1 was reached. At the same time, the product concentrations were also improved so that complete yields were achieved.

An optimized electrotransformation protocol for Lactobacillus jensenii

Engineered bacteria are promising candidates for in situ detection and treatment of diseases. The female uro-genital tract presents several pathologies, such as sexually transmitted diseases or genital cancer, that could benefit from such technology. While bacteria from the gut microbiome are increasingly engineered, the use of chassis isolated from the female uro-genital resident flora has been limited. A major hurdle to implement the experimental throughput required for efficient engineering in these non-model bacteria is their low transformability. Here we report an optimized electrotransformation protocol for Lactobacillus jensenii, one the most widespread species across vaginal microflora. Starting from classical conditions, we optimized buffers, electric field parameters, cuvette type and DNA quantity to achieve an 80-fold improvement in transformation efficiency, with up to 3.5·103 CFUs/μg of DNA in L. jensenii ATCC 25258. We also identify several plasmids that are maintained and support reporter gene expression in L. jensenii. Finally, we demonstrate that our protocol provides increased transformability in three independent clinical isolates of L. jensenii. This work will facilitate the genetic engineering of L. jensenii and enable its use for addressing challenges in gynecological healthcare.

Comparison of mechanistic and hybrid modeling approaches for characterization of a CHO cultivation process: Requirements, pitfalls and solution paths

Despite the advantages of mathematical bioprocess modeling, successful model implementation already starts with experimental planning and accordingly can fail at this early stage. For this study, two different modeling approaches (mechanistic and hybrid) based on a four-dimensional antibody-producing CHO fed-batch process are compared. Overall, 33 experiments are performed in the fractional factorial four-dimensional design space and separated into four different complex data partitions subsequently used for model comparison and evaluation. The mechanistic model demonstrates the advantage of prior knowledge (i.e., known equations) to get informative value relatively independently of the utilized data partition. The hybrid approach displayes a higher data dependency but simultaneously yielded a higher accuracy on all data partitions. Furthermore, our results demonstrate that independent of the chosen modeling framework, a smart selection of only four initial experiments can already yield a very good representation of a full design space independent of the chosen modeling structure. Academic and industry researchers are recommended to pay more attention to experimental planning to maximize the process understanding obtained from mathematical modeling.

The use of predictive models to develop chromatography-based purification processes

Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.

Fermentable sugars production from wheat bran and rye bran: response surface model optimization of dilute sulfuric acid hydrolysis

ABSTRACTOptimization of hydrolysis conditions of lignocellulosic biomass is crucial to able to produce value-added products by fermentation. This study not only determines optimal dilute sulfuric acid (H₂SO₄) hydrolysis conditions of wheat bran (WB) and rye bran (RB) by using one-factor-at-a-time method and subsequently Box-Behnken design but also elucidates chemical composition of hydrolysates yielded under optimal hydrolysis conditions. Based on the results, optimal hydrolysis conditions of WB and RB were 121 and 130°C of temperature, 1/8 and 1/8 w/v of solid to liquid ratio, 2.66 and 1.58% v/v of dilute H₂SO₄ ratio, and 30 and 16 min of implementation time, respectively. Hydrolysates obtained from WB and RB at these conditions contained 72.7 (0.58 g sugar/g biomass) and 89.4 g/L (0.72 g sugar/g biomass) of reducing sugar concentration, respectively. Hydrolysis rates of WB and RB were 87.79 and 91.33%, respectively. Main reducing sugar in RB hydrolysate was glucose with 31.17 g/L (0.25 g glucose/g biomass) while glucose and xylose were the main monosaccharides with 20.90 (0.17 g glucose/g biomass) and 18.69 g/L (0.15 g xylose/g biomass) in WB hydrolysate, respectively. With acidic hydrolysis of WB and RB, inhibitors such as phenolics, 5-Hydroxymethylfurfural, 2-Furaldehyde (not for RB), acetic acid, and formic acid (not for WB) formed. Catalytic efficiency values of H₂SO₄ for WB and RB were 15.2 and 24.4 g /g, respectively, indicating that inhibitor concentration in WB hydrolysate was higher than that of RB. These results indicated that WB and RB have a high potential in production of value-added products by fermentation.

Application of tools and techniques of quality by design in pharmaceutical process

Purpose

The purpose of this article is to demonstrate the application of the tools and techniques of Quality by Design (QbD) approach in an Indian pharmaceutical drug product manufacturing company and to understand the challenges, managerial implications and lessons learned while implementing this initiative.

Design/methodology/approach

This work adopts the Action Research methodology for impurity reduction in a drug product manufacturing company in India by using the tools and techniques of QbD approach. Various QbD tools like Design of experiments, process capability evaluation and control charts were effectively utilized for the study.

Findings

As a part of QbD implementation in the organization, a specific drug product was identified and the impurity level in the product was studied. Significant variables impacting the impurity were identified and the optimum levels for the significant variables were identified through design of experiments. The solutions were implemented and the impurity levels were reduced significantly.

Research limitations/implications

Even though the article is based on a single case study related to tools and techniques of QbD in a single organization in India, the identified problem is a generic product quality related issue for any pharmaceutical drug product manufacturing company. Hence the findings of this research are applicable to pharmaceutical drug manufacturing industry in general.

Originality/value

This article illustrates the systematic usage of various tools and techniques of QbD methodology in a pharmaceutical drug product manufacturing company. The usage of Design of Experiments for process optimization and application of other tools and techniques are ready references for the practitioners and novice users in the field.

A systematic review on potential microbial carbohydrases: current and future perspectives

Various studies have shown that the microbial proteins are often more stable than belongs to other sources like plant and animal origin. Hence, the interest in microbial enzymes has gained much attention due to many potential applications like bioenergy, biofuel production, biobleaching, bioconversion and so on. Additionally, recent trends revealed that the interest in isolating novel microbes from harsh environments have been the main focus of many scientists for various applications. Basically, industrially important enzymes can be categorized into mainly three groups: carbohydrases, proteases, and lipases. Among those, the enzymes especially carbohydrases involved in production of sugars. Carbohydrases include amylases, xylanases, pectinases, cellulases, chitinases, mannases, laccases, ligninases, lactase, glucanase, and glucose oxidase. Thus, here, an approach has been made to highlight five enzymes namely amylase, cellulase, laccase, pectinase, and xylanase from different sources with special emphasis on their properties, mechanism, applications, production optimization, purification, molecular approaches for its enhanced and stable production, and also biotechnological perspectives of its future development. Also, green and sustainable catalytic conversion strategies using nanoparticles of these enzymes have also been discussed. This review will provide insight into the carbohydrases importance and their usefulness that will help to the researchers working in this field.

Polymeric micelles loaded with glyburide and vanillic acid: I. Formulation development, in-vitro characterization and bioavailability studies

The co-formulation of glyburide (Gly) and vanillic acid (VA) as such in the form of nanomedicine has never been explored to treat metabolic diseases including type 2 diabetes mellitus. Both the drugs possess dissolution rate-limited oral bioavailability leading to poor therapeutic efficacy. Hence, co-loading these drugs into a nanocarrier could overcome their poor oral bioavailability related challenges. Owing to this objective, both drugs were co-loaded in amphiphilic polymeric micelles (APMs) and evaluated for their biopharmaceutical outcomes. The APMs were prepared using mPEG-b-PCL/CTAB as a copolymer-surfactant system via the liquid antisolvent precipitation (LAP) method. The design of these APMs were optimized using Box Behnken Design by taking various process/formulation based variables to achieve the desired micellar traits. The release of both the drugs from the optimized co-loaded APMs was compared in different media and displayed a remarkable sustained release profile owing to their hydrophobic interactions with the PCL core. The in vitro cytotoxicity study of co-loaded APMs on Caco-2 cells revealed 70 % cell viability in a concentration-dependent manner. The preventive effects of Gly and VA co-loaded in APMs on glucose uptake was studied in insulin-responsive human HepG2 cells treated with high glucose. The co-loading of both the drugs in optimized APMs exhibited synergistic glucose-lowering activity (p < 0.001) than raw drugs with low cytotoxicity on HepG2 cells within the test concentration. This could be attributed to an increase in the relative oral bioavailability of both the drugs in APMs i.e., 868 % for Gly and 87 % for VA respectively.

Production of an anti-TNFα antibody in murine myeloma cells by perfusion culture

Infliximab is a mouse/human chimeric IgG1 monoclonal antibody which recognizes the proinflammatory cytokine, tumor necrosis factor α (TNFα), and inhibits receptor interactions, thereby decreasing inflammation and autoimmune response in patients. This monoclonal antibody has been successfully used to treat rheumatoid arthritis, ankylosing spondylitis, and psoriatic arthritis. However, the high treatment cost limits patient access to this biotherapy. One alternative to this problem is the use of biosimilars. In this work, we describe the stable expression and physicochemical characterization of an anti-TNFα antibody. While infliximab is produced in recombinant murine SP2/0 cells, our anti-TNFα IgG antibody was expressed in recombinant murine NS0 myeloma cells. The best anti-TNFα antibody-expressing clone was selected from three clone candidates based on the stability of IgG expression levels, specific productivity as well as TNFα-binding activity compared to commercial infliximab. Our results indicate that the selected cell clone, culture medium, and fermentation mode allowed for the production of an anti-TNFα antibody with similar characteristics to the reference commercially available product. An optimization of the selected culture medium by metabolomics may increase the volumetric productivity of the process to satisfy the demand for this product. Further experiments should be performed to evaluate the biological properties of this anti-TNFα antibody. KEY POINTS: • An anti-TNFα antibody was produced in NS0 cells using perfusion culture. • A proprietary chemically defined culture medium was used to replace commercially available protein-free medium. • The purified anti-TNFα antibody was comparable to the reference marketed product.

Design of experiments as a decision tool for cell therapy manufacturing

BACKGROUND AIMS

Cell therapies are costlier to manufacture than small molecules and protein therapeutics because they require multiple manipulations and are often produced in an autologous manner. Strategies to lower the cost of goods to produce a cell therapy could make a significant impact on its total cost.

METHODS

Borrowing from the field of bioprocess development, the authors took a design of experiments (DoE)-based approach to understanding the manufacture of a cell therapy product in pre-clinical development, analyzing main cost factors in the production process. The cells used for these studies were autologous CD4+ T lymphocytes gene-edited using CRISPR/Cas9 and recombinant adeno-associated virus (AAV) to restore normal FOXP3 gene expression as a prospective investigational product for patients with immune dysregulation, polyendocrinopathy, enteropathy, X-linked (IPEX) syndrome.

RESULTS

Using gene editing efficiency as the response variable, an initial screen was conducted for other variables that could influence the editing frequency. The multiplicity of infection (MOI) of AAV and amount of single guide RNA (sgRNA) were the significant factors used for the optimization step to generate a response contour plot. Cost analysis was done for multiple points in the design space to find cost drivers that could be reduced. For the range of values tested (50 000-750 000 vg/cell AAV and 0.8-4 μg sgRNA), editing with the highest MOI and sgRNA yielded the best gene editing frequency. However, cost analysis showed the optimal solution was gene editing at 193 000 vg/cell AAV and 1.78 μg sgRNA.

CONCLUSIONS

The authors used DoE to define key factors affecting the gene editing process for a potential investigational therapeutic, providing a novel and faster data-based approach to understanding factors driving complex biological processes. This approach could be applied in process development and aid in achieving more robust strategies for the manufacture of cellular therapeutics.

Optimization of an O2-balanced bioartificial pancreas for type 1 diabetes using statistical design of experiment

A bioartificial pancreas (BAP) encapsulating high pancreatic islets concentration is a promising alternative for type 1 diabetes therapy. However, the main limitation of this approach is O2 supply, especially until graft neovascularization. Here, we described a methodology to design an optimal O2-balanced BAP using statistical design of experiment (DoE). A full factorial DoE was first performed to screen two O2-technologies on their ability to preserve pseudo-islet viability and function under hypoxia and normoxia. Then, response surface methodology was used to define the optimal O2-carrier and islet seeding concentrations to maximize the number of viable pseudo-islets in the BAP containing an O2-generator under hypoxia. Monitoring of viability, function and maturation of neonatal pig islets for 15 days in vitro demonstrated the efficiency of the optimal O2-balanced BAP. The findings should allow the design of a more realistic BAP for humans with high islets concentration by maintaining the O2 balance in the device.

Bioengineering Outlook on Cultivated Meat Production

Cultured meat (also referred to as cultivated meat or cell-based meat)-CM-is fabricated through the process of cellular agriculture (CA), which entails application of bioengineering, i.e., tissue engineering (TE) principles to the production of food. The main TE principles include usage of cells, grown in a controlled environment provided by bioreactors and cultivation media supplemented with growth factors and other needed nutrients and signaling molecules, and seeded onto the immobilization elements-microcarriers and scaffolds that provide the adhesion surfaces necessary for anchor-dependent cells and offer 3D organization for multiple cell types. Theoretically, many solutions from regenerative medicine and biomedical engineering can be applied in CM-TE, i.e., CA. However, in practice, there are a number of specificities regarding fabrication of a CM product that needs to fulfill not only the majority of functional criteria of muscle and fat TE, but also has to possess the sensory and nutritional qualities of a traditional food component, i.e., the meat it aims to replace. This is the reason that bioengineering aimed at CM production needs to be regarded as a specific scientific discipline of a multidisciplinary nature, integrating principles from biomedical engineering as well as from food manufacturing, design and development, i.e., food engineering. An important requirement is also the need to use as little as possible of animal-derived components in the whole CM bioprocess. In this review, we aim to present the current knowledge on different bioengineering aspects, pertinent to different current scientific disciplines but all relevant for CM engineering, relevant for muscle TE, including different cell sources, bioreactor types, media requirements, bioprocess monitoring and kinetics and their modifications for use in CA, all in view of their potential for efficient CM bioprocess scale-up. We believe such a review will offer a good overview of different bioengineering strategies for CM production and will be useful to a range of interested stakeholders, from students just entering the CA field to experienced researchers looking for the latest innovations in the field.

A statistical approach to boost soluble expression of E. coli-derived virus-like particles in shake-flask cultivation

Hepatitis B core virus-like particles (HBc-VLP) have been widely used as carrier platforms to present an epitope of interest. Escherichia coli expression system is cost effective and produces high yields of recombinant protein. However major drawbacks include difficulties in obtaining soluble expression and tendency to form inclusion bodies. To boost solubility of proteins during expression of E. coli-derived HBc-VLPs carrying EBNA1 epitope, a statistical approach involving fractional factorial design (FFD) and response surface methodology (RSM) was used. For the first time, this approach was applied to quantitatively determine the impact of key parameters in shake-flask cultivation. Expression conditions including post-induction temperature and shaker-speed, and cell density at induction were optimized. Based on native agarose gel electrophoresis, optimized soluble protein cellular yield was 210.5mgg^-1 dry cell mass and volumetric yield was 272mgL^-1 of culture media. Findings highlight: 1) the significant interaction between post-induction temperature and shaker-speed on production, and; 2) sufficient oxygen level is required during induction. It is concluded that this statistical approach can be practically applied to optimize expression of HBc-VLP in shake-flask cultivation, and to determine key parameters for large-scale productions.

Improving Antibacterial Activity of a HtrA Protease Inhibitor JO146 against Helicobacter pylori: A Novel Approach Using Microfluidics-Engineered PLGA Nanoparticles

Nanoparticle drug delivery systems have emerged as a promising strategy for overcoming limitations of antimicrobial drugs such as stability, bioavailability, and insufficient exposure to the hard-to-reach bacterial drug targets. Although size is a vital colloidal feature of nanoparticles that governs biological interactions, the absence of well-defined size control technology has hampered the investigation of optimal nanoparticle size for targeting bacterial cells. Previously, we identified a lead antichlamydial compound JO146 against the high temperature requirement A (HtrA) protease, a promising antibacterial target involved in protein quality control and virulence. Here, we reveal that JO146 was active against Helicobacter pylori with a minimum bactericidal concentration of 18.8–75.2 µg/mL. Microfluidic technology using a design of experiments approach was utilized to formulate JO146-loaded poly(lactic-co-glycolic) acid nanoparticles and explore the effect of the nanoparticle size on drug delivery. JO146-loaded nanoparticles of three different sizes (90, 150, and 220 nm) were formulated with uniform particle size distribution and drug encapsulation efficiency of up to 25%. In in vitro microdilution inhibition assays, 90 nm nanoparticles improved the minimum bactericidal concentration of JO146 two-fold against H. pylori compared to the free drug alone, highlighting that controlled engineering of nanoparticle size is important in drug delivery optimization.

From the Discovery of Extremozymes to an Enzymatic Product: Roadmap Based on Their Applications

With the advent of the industrial revolution, the use of toxic compounds has grown exponentially, leading to a considerable pollution of the environment. Consequently, the development of more environmentally conscious technologies is an urgent need. Industrial biocatalysis appears as one potential solution, where a higher demand for more robust enzymes aims to replace toxic chemical catalysts. To date, most of the commercially available enzymes are of mesophilic origin, displaying optimal activity in narrow ranges of temperature and pH (i.e., between 20°C and 45°C, neutral pH), limiting their actual application under industrial reaction settings, where they usually underperform, requiring larger quantities to compensate loss of activity. In order to obtain novel biocatalysts better suited for industrial conditions, an efficient solution is to take advantage of nature by searching and discovering enzymes from extremophiles. These microorganisms and their macromolecules have already adapted to thrive in environments that present extreme physicochemical conditions. Hence, extremophilic enzymes stand out for showing higher activity, stability, and robustness than their mesophilic counterparts, being able to carry out reactions at nonstandard conditions. In this brief research report we describe three examples to illustrate a stepwise strategy for the development and production of commercial extremozymes, including a catalase from an Antarctic psychrotolerant microorganism, a laccase from a thermoalkaliphilic bacterium isolated from a hot spring and an amine-transaminase from a thermophilic bacterium isolated from a geothermal site in Antarctica. We will also explore some of their interesting biotechnological applications and comparisons with commercial enzymes.

Clever Experimental Designs: Shortcuts for Better iPSC Differentiation

For practical use of pluripotent stem cells (PSCs) for disease modelling, drug screening, and regenerative medicine, the cell differentiation process needs to be properly refined to generate end products with consistent and high quality. To construct and optimize a robust cell-induction process, a myriad of cell culture conditions should be considered. In contrast to inefficient brute-force screening, statistical design of experiments (DOE) approaches, such as factorial design, orthogonal array design, response surface methodology (RSM), definitive screening design (DSD), and mixture design, enable efficient and strategic screening of conditions in smaller experimental runs through multifactorial screening and/or quantitative modeling. Although DOE has become routinely utilized in the bioengineering and pharmaceutical fields, the imminent need of more detailed cell-lineage specification, complex organoid construction, and a stable supply of qualified cell-derived material requires expedition of DOE utilization in stem cell bioprocessing. This review summarizes DOE-based cell culture optimizations of PSCs, mesenchymal stem cells (MSCs), hematopoietic stem cells (HSCs), and Chinese hamster ovary (CHO) cells, which guide effective research and development of PSC-derived materials for academic and industrial applications.

Scaling-up production of plant endophytes in bioreactors: concepts, challenges and perspectives

The benefit of microorganisms to humans, animals, insects and plants is increasingly recognized, with intensified microbial endophytes research indicative of this realization. In the agriculture industry, the benefits are tremendous to move towards sustainable crop production and minimize or circumvent the use of chemical fertilizers and pesticides. The research leading to the identification of potential plant endophytes is long and arduous and for many researchers the challenge is ultimately in scale-up production. While many of the larger agriculture and food industries have their own scale-up and manufacturing facilities, for many in academia and start-up companies the next steps towards production have been a stumbling block due to lack of information and understanding of the processes involved in scale-up fermentation. This review provides an overview of the fermentation process from shake flask cultures to scale-up and the manufacturing steps involved such as process development optimization (PDO), process hazard analysis (PHA), pre-, in- and post-production (PIP) challenges and finally the preparation of a technology transfer package (TTP) to transition the PDO to manufacturing. The focus is on submerged liquid fermentation (SLF) and plant endophytes production by providing original examples of fungal and bacterial endophytes, plant growth promoting Penicillium sp. and Streptomyces sp. bioinoculants, respectively. We also discuss the concepts, challenges and future perspectives of the scale-up microbial endophyte process technology based on the industrial and biosafety research platform for advancing a massive production of next-generation biologicals in bioreactors.

A bioprocess perspective on the production of secondary metabolites by Streptomyces in submerged co-cultures

Filamentous microorganisms are potent sources of bioactive secondary metabolites, the molecules formed in response to complex environmental signals. The chemical diversity encoded in microbial genomes is only partially revealed by following the standard microbiological approaches. Mimicking the natural stimuli through laboratory co-cultivation is one of the most effective methods of awakening the formation of high-value metabolic products. Whereas the biosynthetic outcomes of co-cultures are reviewed extensively, the bioprocess aspects of such efforts are often overlooked. The aim of the present review is to discuss the submerged co-cultivation strategies used for triggering and enhancing secondary metabolites production in Streptomyces, a heavily investigated bacterial genus exhibiting an impressive repertoire of secondary metabolites, including a vast array of antibiotics. The previously published studies on influencing the biosynthetic capabilities of Streptomyces through co-cultivation are comparatively analyzed in the bioprocess perspective, mainly with the focus on the approaches of co-culture initiation, the experimental setup, the design of experimental controls and the ways of influencing the outcomes of co-cultivation processes. These topics are discussed in the general context of secondary metabolites production in submerged microbial co-cultures by referring to the Streptomyces-related studies as illustrative examples.

Design of transfections: Implementation of design of experiments for cell transfection fine tuning

Transfection is the process by which nucleic acids are introduced into eukaryotic cells. This is fundamental in basic research for studying gene function and modulation of gene expression as well as for many bioprocesses in the manufacturing of clinical‐grade recombinant biologics from cells. Transfection efficiency is a critical parameter to increase biologics' productivity; the right protocol has to be identified to ensure high transfection efficiency and therefore high product yield. Design of experiments (DoE) is a mathematical method that has become a key tool in bioprocess development. Based on the DoE method, we developed an operational flow that we called “Design of Transfections” (DoT) for specific transfection modeling and identification of the optimal transfection conditions. As a proof of principle, we applied the DoT workflow to optimize a cell transfection chemical protocol for neural progenitors, using polyethyleneimine (PEI). We simultaneously varied key influencing factors, namely concentration and type of PEI, DNA concentration, and cell density. The transfection efficiency was measured by fluorescence imaging followed by automatic counting of the green fluorescent transfected cells. Taking advantage of the DoT workflow, we developed a new simple, efficient, and economically advantageous PEI transfection protocol through which we were able to obtain a transfection efficiency of 34%.

Yarrowia lipolytica Bioprocess Development: From Flask to Bioreactor

Yarrowia lipolytica produces a range of valuable biotechnological products from natural metabolites and enzymes to heterologous proteins. The production of these products is affected by medium composition and various environmental factors. Here we describe bioprocess development for a recombinant laccase production by Y. lipolytica. At first, response surface methodology (RSM), as a statistical technique for design of experiment (DOE), is used for the optimization of medium composition in flask level. Then, results of RSM are applied to increase laccase production in controlled conditions of the bioreactor.

Thermal treatment process of PET bottles filaments using industrial design of experiments

Purpose

The purpose of this paper is to present the application of Design of Experiments techniques for the analysis of operating parameters of an industrial oven for the heat treatment process of polyethylene terephthalate (PET) bottle filaments.

Design/methodology/approach

The focus is on evaluating new ways of operating the transformation process. The main issue is to raise what are the variables interfering with the performance of the oven. The complete 2k factorial for three factors of control was used to analyze the behavior of these variables and their relationships in the specific response parameter for the process.

Findings

The results presented in this work allow the company to have greater knowledge about the operation of the equipment. The study showed possibilities of 14.8% energy reduction.

Research limitations/implications

The heat treatment activity was characterized as a critical point in the production process, and techniques with empirical approaches, based on statistical techniques, was an opportunity that the company has to improve the execution of activities without major investments for the quality of the final product. The application of statistical quality techniques showed to be very promising.

Originality/value

The fact that the study was conducted using subjective quality performance makes this work different from others presented in the literature, showing the possibility to apply Design of Experiments using main control factors based on the opinion of experienced personnel involved in the process analyzed.

Induced Pluripotent Stem Cell-Derived Endothelial Networks Accelerate Vascularization But Not Bone Regeneration

Vascularization is critical for engineering mineralized tissues. It has been previously shown that biomaterials containing preformed endothelial networks anastomose to host vasculature following implantation. However, the networks alone may not increase regeneration. In addition, a clinically applicable source of cells for vascularization is needed. In this study, vascular networks were generated from endothelial cells (ECs) derived from human induced pluripotent stem cells (iPSCs). Network formation by iPSC-ECs within fibrin gels was investigated in a mesenchymal stem cells (MSCs) coculture spheroid model. Statistical design of experiments technique was evaluated for its predicting capability during the optimization of experimental parameters. The prevascularized units were combined with hydroxyapatite nanoparticles to develop a vascularized composite hydrogel that was implanted in a rodent critical-sized cranial defect model. Immunohistological staining for human-specific CD31 at week 1 indicated the presence and maintenance of the implanted vessels. At 8 weeks, the prevascularized systems resulted in higher vessel density over MSC-only scaffolds. The implanted vessels appeared to establish flow with host vasculature. While there was a slight increase in bone volume in the prevascularized bone construct compared to MSC-only bone constructs, there was not a profound increase in bone regeneration. These results show that scaffolds with network structures can be generated from ECs derived from iPSC and that the networks survive and inosculate with the host postimplantation in a bone model. Impact statement Vascularization is critical for engineering bone. Prevascularized scaffolds have been shown to improve postimplantation vascularization. Herein, vascularized networks were generated from induced pluripotent cells derived from endothelial cells. These vascularized units were combined with a fibrin/hydroxyapatite scaffold to develop a prevascularized construct for bone regeneration. Implantation of these scaffolds in a small animal cranial defect model resulted in network inosculation and increased vascularization, but exhibited only a limited effect on bone formation. This study provides insight into the challenges of generating vascularized bone.

Designing a Strategy for pH Control to Improve CHO Cell Productivity in Bioreactor

BACKGROUND

Drastic pH drop is a common consequence of scaling up a mammalian cell culture process, where it may affect the final performance of cell culture. Although CO2 sparging and base addition are used as common approaches for pH control, these strategies are not necessarily successful in large scale bioreactors due to their effect on osmolality and cell viability. Accordingly, a series of experiments were conducted using an IgG1 producing Chinese Hamster Ovary (CHO-S) cell culture in 30 L bioreactor to assess the efficiency of an alternative strategy in controlling culture pH.

METHODS

Factors inducing partial pressure of CO2 and lactate accumulation (as the main factors altering culture pH) were assessed by Plackett-Burman design to identify the significant ones. As culture pH directly influences process productivity, protein titer was measured as the response variable. Subsequently, Central Composite Design (CCD) was employed to obtain a model for product titer prediction as a function of individual and interaction effects of significant variables.

RESULTS

The results indicated that the major factor affecting pH is non-efficient CO2 removal. CO2 accumulation was found to be affected by an interaction between agitation speed and overlay air flow rate. Accordingly, after increasing the agitation speed and headspace aeration, the culture pH was successfully maintained in the range of 6.95-7.1, resulting in 51% increase in final product titer. Similar results were obtained during 250 L scale bioreactor culture, indicating the scalability of the approach.

CONCLUSION

The obtained results showed that pH fluctuations could be effectively controlled by optimizing CO2 stripping.

Digital Twin Application for Model-Based DoE to Rapidly Identify Ideal Process Conditions for Space-Time Yield Optimization

The fast exploration of a design space and identification of the best process conditions facilitating the highest space-time yield are of great interest for manufacturers. To obtain this information, depending on the design space, a large number of practical experiments must be performed, analyzed, and evaluated. To reduce this experimental effort and increase the process understanding, we evaluated a model-based design of experiments to rapidly identify the optimum process conditions in a design space maximizing space-time yield. From a small initial dataset, hybrid models were implemented and used as digital bioprocess twins, thus obtaining the recommended optimal experiment. In cases where these optimum conditions were not covered by existing data, the experiment was carried out and added to the initial data set, re-training the hybrid model. The procedure was repeated until the model gained certainty about the best process conditions, i.e., no new recommendations. To evaluate this workflow, we utilized different initial data sets and assessed their respective performances. The fastest approach for optimizing the space-time yield in a three-dimensional design space was found with five initial experiments. The digital twin gained certainty after four recommendations, leading to a significantly reduced experimental effort compared to other state-of-the-art approaches. This highlights the benefits of in silico design space exploration for accelerating knowledge-based bioprocess development, and reducing the number of hands-on experiments, time, energy, and raw materials.