Vegan grade medium component screening and concentration optimization for the fermentation of the probiotic strain Lactobacillus paracasei IMC 502® using Design of Experiments.

Lactobacillus paracasei IMC502® is a commercially successful probiotic strain. However, there are no reports that investigate growth medium composition in relation to improved biomass production for this strain. The major outcome of the present study is the design and optimization of a growth medium based on vegan components to be used in the cultivation of Lactobacillus paracasei IMC502®, by using Design of Experiments. Besides comparing different carbon sources, the use of plant-based peptones as nitrogen sources was considered. In particular, the use of guar peptone as the main nitrogen source, in the optimization of fermentation media for the production of probiotics, could replace other plant peptones (e.g. potato, rice, wheat, and soy) which are part of the human diet, thereby avoiding an increase in product and process prices. A model with R2 and adjusted R2 values higher than 95% was obtained. Model accuracy was equal to 94.11%. The vegan-optimized culture medium described in this study increased biomass production by about 65% compared to growth on De Man-Rogosa-Sharpe (MRS) medium. Moreover, this approach showed that most of the salts and trace elements generally present in MRS are not affecting biomass production, thus a simplified medium preparation can be proposed with higher probiotic biomass yield and titer. The possibility to obtain viable lactic acid bacteria at high density from vegetable derived nutrients will be of great interest to specific consumer communities, opening the way to follow this approach with other probiotics of impact for human health.

Sol-gel and Pechini niobium modified: synthesis, characterization and application in the 2,4-D herbicide degradation.

In this work, a comparison was made between the synthesis of niobium-based materials (Nb2O5), both in terms of material characterization and catalytic performance. The methods used were chemical mixtures: modified sol-gel and Pechini. The materials were calcined at different temperatures (753, 873 and 993K) and characterized by the following techniques: photoacousticspectroscopy (PAS), zero charge point (pHPZC), scanning electron microscopy (SEM/EDS), thermogravimetric analysis (TGA/DTG) and X-ray diffraction (XRD). The photocatalytic process was carried out to evaluate the degradation of 2,4-dichlorophenoxyacetic acid (2,4-D) under UV radiation (250 W mercury vapor lamp) and different experimental conditions. In addition, to better understand the influence of parameters such as pH, catalyst concentration (0.2, 0.5 and 0.8 g L-1) and calcination temperature, a Design of Experiments (DoE) was used. The results indicated that despite having similar structures and phases in the XRD analysis, the morphology presents two distinct surfaces, due to the preparation method. Differences in the synthesis method affected the catalytic activity in the parameters studied. Although the zero charge point values are close (6.18-6.36), we observed differences in the band gap depending on the calcination temperature. In the optimal condition studied, the catalyst prepared by the sol-gel method obtained the best results.

Design space determination to optimize DNA complexation and full capsid formation in transient rAAV manufacturing.

Recombinant adeno-associated virus (rAAV) vectors are a promising platform for in vivo gene therapies. However, cost-effective, well-characterized processes necessary to manufacture rAAV therapeutics are challenging to develop without an understanding of how process parameters (PPs) affect rAAV product quality attributes (PQAs). In this work, a central composite orthogonal experimental design was employed to examine the influence of four PPs for transient transfection complex formation (polyethylenimine:DNA [PEI:DNA] ratio, total DNA/cell, cocktail volume, and incubation time) on three rAAV PQAs related to capsid content (vector genome titer, vector genome:capsid particle ratio, and two-dimensional vector genome titer ratio). A regression model was established for each PQA using partial least squares, and a design space (DS) was defined in which Monte Carlo simulations predicted < 1% probability of failure (POF) to meet predetermined PQA specifications. Of the three PQAs, viral genome titer was most strongly correlated with changes in complexation PPs. The DS and acceptable PP ranges were largest when incubation time and cocktail volume were kept at mid-high setpoints, and PEI:DNA ratio and total DNA/cell were at low-mid setpoints. Verification experiments confirmed model predictive capability, and this work establishes a framework for studying other rAAV PPs and their relationship to PQAs.

Estimation of measurement uncertainty for the quantification of protein by ID-LC-MS/MS.

The emergence of mass spectrometry (MS)-based methods to quantify proteins for clinical applications has led to the need for accurate and consistent measurements. To meet the clinical needs of MS-based protein results, it is important that the results are traceable to higher-order standards and methods and have defined uncertainty values. Therefore, we outline a comprehensive approach for the estimation of measurement uncertainty of a MS-based procedure for the quantification of a protein biomarker. Using a bottom-up approach, which is the model outlined in the "Guide to the Expression of Uncertainty of Measurement" (GUM), we evaluated the uncertainty components of a MS-based measurement procedure for a protein biomarker in a complex matrix. The cause-and-effect diagram of the procedure is used to identify each uncertainty component, and statistical equations are derived to determine the overall combined uncertainty. Evaluation of the uncertainty components not only enables the calculation of the measurement uncertainty but can also be used to determine if the procedure needs improvement. To demonstrate the use of the bottom-up approach, the overall combined uncertainty is estimated for the National Institute of Standards and Technology (NIST) candidate reference measurement procedure for albumin in human urine. The results of the uncertainty approach are applied to the determination of uncertainty for the certified value for albumin in candidate NIST Standard Reference Material® (SRM) 3666. This study provides a framework for measurement uncertainty estimation of a MS-based protein procedure by identifying the uncertainty components of the procedure to derive the overall combined uncertainty.

Degradation pathways and impurity profiling of the anticancer drug apalutamide by HPLC and LC-MS/MS and separation of impurities using Design of Experiments.

Apalutamide, an androgen receptor inhibitor, is used to treat prostate cancer. A stability-indicating high-performance liquid chromatography method was developed for the estimation of assay and organic impurities of apalutamide in drug substance and in tablet dosages using Design of Experiments. The chromatographic separation was achieved within 30 min using Atlantis dC18 , 100 × 4.6 mm, 3.0 µm and the binary gradient program (10 mm KH2 PO4 , pH 3.5; acetonitrile). The detection wavelength, flow rate, column temperature and injection volume used were 270 nm, 1.0 ml/min, 45°C and 10 µl, respectively. The interaction of independent variables (pH, column temperature and flow rate) and their influences on HPLC parameters were studied using a central composite design, and then the peak separation and elution behaviors between apalutamide and its seven impurities were determined. The method validation was performed for linearity, detection limit, quantitation limit, accuracy, precision and robustness as per the International Conference on Harmonization. A high-quality recovery with good precision (91.7-106.0%) and correlations (r2 > 0.997) within a linear range of 0.12-2.24 µg/ml (0.05-0.3%, w/w) were achieved consistently for assay and organic impurities of apalutamide. The stability-indicating characteristics of the proposed method were assessed through forced degradation and mass balance studies. An effort was made to figure out the chemical structures of newly formed degradation products (DP1-DP5) using LC-MS/MS.

Machine Learning-Enabled NIR Spectroscopy. Part 3: Hyperparameter by Design (HyD) Based ANN-MLP Optimization, Model Generalizability, and Model Transferability.

Data variations, library changes, and poorly tuned hyperparameters can cause failures in data-driven modelling. In such scenarios, model drift, a gradual shift in model performance, can lead to inaccurate predictions. Monitoring and mitigating drift are vital to maintain model effectiveness. USFDA and ICH regulate pharmaceutical variation with scientific risk-based approaches. In this study, the hyperparameter optimization for the Artificial Neural Network Multilayer Perceptron (ANN-MLP) was investigated using open-source data. The design of experiments (DoE) approach in combination with target drift prediction and statistical process control (SPC) was employed to achieve this objective. First, pre-screening and optimization DoEs were conducted on lab-scale data, serving as internal validation data, to identify the design space and control space. The regression performance metrics were carefully monitored to ensure the right set of hyperparameters was selected, optimizing the modelling time and storage requirements. Before extending the analysis to external validation data, a drift analysis on the target variable was performed. This aimed to determine if the external data fell within the studied range or required retraining of the model. Although a drift was observed, the external data remained well within the range of the internal validation data. Subsequently, trend analysis and process monitoring for the mean absolute error of the active content were conducted. The combined use of DoE, drift analysis, and SPC enabled trend analysis, ensuring that both current and external validation data met acceptance criteria. Out-of-specification and process control limits were determined, providing valuable insights into the model's performance and overall reliability. This comprehensive approach allowed for robust hyperparameter optimization and effective management of model lifecycle, crucial in achieving accurate and dependable predictions in various real-world applications.

A simple and effective method to purify and activate T cells for successful generation of chimeric antigen receptor T (CAR-T) cells from patients with high monocyte count.

BACKGROUND: Chimeric antigen receptor T (CAR-T) cells are genetically modified T cells with redirected specificity and potent T-cell-mediated cytotoxicity toward malignant cells. Despite several CAR-T products being approved and commercialized in the USA, Europe, and China, CAR-T products still require additional optimization to ensure reproducible and cost-effective manufacture. Here, we investigated the critical parameters in the CD3+ T-cell isolation process that significantly impacted CAR-T manufacturing's success. METHODS: CAR-T cells were prepared from cryopreserved peripheral blood mononuclear cells (PBMC). The thawed PBMC was rested overnight before the CD3+ T cell isolation process using CTS™ Dynabeads™ CD3/CD28. Different isolation media, cell-bead co-incubation time, and cell density were examined in this study. Activated CD3+ T cells were transduced with a gamma retroviral vector carrying the CD19 or BCMA CAR sequence. The CAR-T cells proliferated in a culture medium supplemented with interleukin 2 (IL-2). RESULTS: CD14+ monocytes hindered T-cell isolation when X-VIVO 15 basic medium was used as the selection buffer. The activation of T cells was blocked because monocytes actively engulfed CD3/28 beads. In contrast, when DPBS was the selection medium, the T-cell isolation and activation were no longer blocked, even in patients whose PBMC contained abnormally high CD14+ monocytes and a low level of CD3+ T cells. CONCLUSIONS: In this study, we discovered that selecting CD3+ T-cell isolation media is critical for improving T-cell activation, transduction, and CAR-T proliferation. Using DPBS as a CD3+ T cell isolation buffer significantly improved the success rate and shortened the duration of CAR-T production. The optimized process has been successfully applied in our ongoing clinical trials. Trial registration NCT03798509: Human CD19 Targeted T Cells Injection Therapy for Relapsed and Refractory CD19-positive Leukemia. Date of registration: January 10, 2019. NCT03720457: Human CD19 Targeted T Cells Injection (CD19 CAR-T) Therapy for Relapsed and Refractory CD19-positive Lymphoma. Date of registration: October 25, 2018. NCT04003168: Human BCMA Targeted T Cells Injection Therapy for BCMA-positive Relapsed/Refractory Multiple Myeloma. Date of registration: July 1, 2019.

DoE-based validation of a HPLC-UV method for quantification of rotigotine nanocrystals: Application to in vitro dissolution and ex vivo nasal permeation studies.

The current work is focused on optimization, development, and validation of a sensitive and specific reversed-phase high-performance liquid chromatography (RP-HPLC) method for the estimation of rotigotine (RTG) in bulk and nanoformulations. The RP-HPLC method was effectively optimized using the concepts of design of experiments. Critical method variables (CMVs) were screened using Plackett-Burman design. Box-Behnken, a surface response methodology-based design, was further used for the optimization of CMVs with the number of theoretical plates and retention time (min) as responses. The optimized chromatographic conditions for the RP-HPLC method were: acetonitrile proportion: 54% v/v, pH of buffer: 5.0 (10 mM), and flow rate: 0.65 mL/min. The number of theoretical plates and retention time in the study were found to be 11206 and 7.65 min, respectively. The developed method exhibited good linearity (R2 = 0.9995) within a range of 25-600 ng/mL and LOD and LOQ were found to be 9 and 12 ng/mL, respectively. The developed RP-HPLC method was found sensitive, accurate, precise, specific, robust, and stability indicating according to the regulatory guidelines. The validated method was efficiently applied for in vitro dissolution study, ex vivo nasal permeation study, and estimation of drug content of RTG nanocrystals.

Robust parameter design of human induced pluripotent stem cell differentiation protocols defines lineage-specific induction of anterior-posterior gut tube endodermal cells.

Tissues and cells derived from pluripotent stem cells (PSC) are likely to become widely used in disease modeling, drug screening, and regenerative medicine. For these applications, the in vitro PSC differentiation process must be elaborately investigated and controlled to reliably obtain the desired end products. However, because traditional experimental methods, such as one factor at a time or brute-force approaches, are impractical for detailed screening of complex PSC cultivation conditions, more strategic and effective screening based on statistical design of experiments (DOE) ought to be indispensable. Among various DOE approaches, we regard robust parameter design (RPD) as particularly suited for differentiation protocol optimization due to its suitability for multifactorial screening. We confirmed the adaptability of RPD for investigating human induced PSC lineage specification toward anterior-posterior gut tube endodermal cells and clarified both the contribution of each cell signaling pathway and the effect of cell signaling condition alteration on marker RNA expression levels, while increasing the efficiency of the screening in 243-fold (18 vs 4374) compared with that of a brute-force approach. Specific induction of anterior foregut, hepatic, pancreatic, or mid-hindgut cells was achieved using seven iPSC strains with the optimal culture protocols established on the basis of RPD analysis. RPD has the potential to enable efficient construction and optimization of PSC differentiation protocols, and its use is recommended from fundamental research to mass production of PSC-derived products.

Optimization of ultrasound-assisted production of ergosterol from Penicillium brevicompactum by Taguchi statistical method.

Ergosterol as a primary metabolite and precursor of vitamin D2, is the most plentiful mycosterols in fungal cell membrane. Process optimization to increase the yield and productivity of biological products is a topic of interest. Ultrasonic waves have many applications in biotechnology, like cell disruption, and enhancement of primary and secondary metabolites production. This study disclosed an optimal condition for ultrasound-assisted production (UAP) of ergosterol from Penicillium brevicompactum MUCL 19,011 using L9 Taguchi statistical method. The intensity (IS), time of sonication (TS), treatment frequency (TF), and number of days of treatment (DT) were allocated to study the effects of ultrasound on ergosterol production. The results were analyzed using Minitab version 19. The maximum ergosterol, 11 mg/g cell dry weight (CDW), was produced on the tenth day while all factors were at a low level. The days of treatment with a contribution of 45.48% was the most significant factor for ergosterol production. For the first time, this study revealed the positive effect of ultrasound on the production of ergosterol. Ergosterol production increased 73% (4.63 mg/g CDW) after process optimization. Finally, a mathematical model of ultrasound factors with a regression coefficient of R2 = 0.978 was obtained for the ergosterol production during ultrasound treatment.

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%.

Design of experiment (DOE) applied to artificial neural network architecture enables rapid bioprocess improvement.

Modern bioprocess development employs statistically optimized design of experiments (DOE) and regression modeling to find optimal bioprocess set points. Using modeling software, such as JMP Pro, it is possible to leverage artificial neural networks (ANNs) to improve model accuracy beyond the capabilities of regression models. Herein, we bridge the gap between a DOE skill set and a machine learning skill set by demonstrating a novel use of DOE to systematically create and evaluate ANN architecture using JMP Pro software. Additionally, we run a mammalian cell culture process at historical, one factor at a time, standard least squares regression, and ANN-derived set points. This case study demonstrates the significant differences between one factor at a time bioprocess development, DOE bioprocess development and the relative power of linear regression versus an ANN-DOE hybrid modeling approach.

Optimization of in-line near-infrared measurement for practical real time monitoring of coating weight gain using design of experiments.

This study was conducted to develop an in-line near-infrared (NIR) spectroscopy approach that allows real time quantitative analysis of the coating weight gain on a moving tablet surface during a coating process where talc is used. A holder directly inserting a diffuse reflectance probe into a coating pan was designed, and the optimal measurement conditions were identified using the design of experiments (DoE). The surface of the probe was kept clean of coating droplets at a maximum distance between the probe and the holder of 272.5 mm, leading to the acquisition of accurate spectral data. Under this condition, partial least squares regression (PLSR) was developed using the spectra from 7197 to 6233 cm-1, which covers the specific peaks for the core tablet and the coating solution. Under the same conditions, least squares regression (LSR) was developed using the univariate predictive analysis of the single absorption spectrum of talc at 7181 cm-1. In a comparison of the accuracy of the two models, PLSR was found to be more accurate as a result of testing the significance of differences between these distributions in terms of the root mean square errors of prediction (RMSEP) using a randomization t-test. Additionally, it confirmed that the predicted weight gain using NIR spectroscopy was correlated with the coating thickness measured using micro-CT. In conclusion, this study developed an in-line NIR measurement approach for the real-time monitoring of the coating weight gain of tablets and optimized the conditions by evaluating the effect of various factors.

Sustained release of curcumin self-emulsifying drug delivery system (SEDDS) from solvent-cast Soluplus® films.

The objective of the present study was to investigate the feasibility of formulating and loading Curcumin SEDDS (Self-Emulsified Drug Delivery Systems) into films made from Soluplus® as the film-forming polymer. Films with up to 30% of Curcumin SEDDS were prepared by the solvent casting technique and analyzed for their mechanical and dissolution properties. A nine-run, two-factor, three-level factorial design was utilized to investigate the effect of SEDDS load (10, 20, and 30% w/w) and film thickness (10, 25, and 40 mils) on the tensile strength, elongation, and adhesiveness of the films. The dissolution profile of the films was also investigated by a USP Type 1 method. SEDDS loading was found to plasticize Soluplus® and to yield transparent films of good mechanical properties. Increasing SEDDS load, however, was found to reduce the tensile strength of the films, while increasing their adhesiveness and elongation. On the other hand, while an increase in film thickness was found to increase the tensile strength of the films, it reduced the elongation capacity of the films. Loading SEDDS into Soluplus® films was also found to sustain their release over 6 h, where a significant delay in release was found at lower SEDDS loads. This study demonstrated that Soluplus® can be used not only to formulate SEDDS into polymeric films but also to sustain their release over an extended time.

Applying Statistical Design of Experiments To Understanding the Effect of Growth Medium Components on Cupriavidus necator H16 Growth.

Cupriavidus necator H16 is gaining significant attention as a microbial chassis for range of biotechnological applications. While the bacterium is a major producer of bioplastics, its lithoautotrophic and versatile metabolic capabilities make the bacterium a promising microbial chassis for biofuels and chemicals using renewable resources. It remains necessary to develop appropriate experimental resources to permit controlled bioengineering and system optimization of this microbe. In this study, we employed statistical design of experiments to gain understanding of the impact of components of defined media on C. necator growth and built a model that can predict the bacterium's cell density based on medium components. This highlighted medium components, and interaction between components, having the most effect on growth: fructose, amino acids, trace elements, CaCl2, and Na2HPO4 contributed significantly to growth (t values of <-1.65 or >1.65); copper and histidine were found to interact and must be balanced for robust growth. Our model was experimentally validated and found to correlate well (r2 = 0.85). Model validation at large culture scales showed correlations between our model-predicted growth ranks and experimentally determined ranks at 100 ml in shake flasks (ρ = 0.87) and 1 liter in a bioreactor (ρ = 0.90). Our approach provides valuable and quantifiable insights on the impact of medium components on cell growth and can be applied to model other C. necator responses that are crucial for its deployment as a microbial chassis. This approach can be extended to other nonmodel microbes of medical and industrial biotechnological importance.IMPORTANCE Chemically defined media (CDM) for cultivation of C. necator vary in components and compositions. This lack of consensus makes it difficult to optimize new processes for the bacterium. This study employed statistical design of experiments (DOE) to understand how basic components of defined media affect C. necator growth. Our growth model predicts that C. necator can be cultivated to high cell density with components held at low concentrations, arguing that CDM for large-scale cultivation of the bacterium for industrial purposes will be economically competitive. Although existing CDM for the bacterium are without amino acids, addition of a few amino acids to growth medium shortened lag phase of growth. The interactions highlighted by our growth model show how factors can interact with each other during a process to positively or negatively affect process output. This approach is efficient, relying on few well-structured experimental runs to gain maximum information on a biological process, growth.

Optimization and validation of a blocking ELISA for quantitation of anti-rabies immunoglobulins in multispecies sera.

We developed a fast, rabies virus-free, in vitro method, based on a blocking ELISA (bELISA), to detect and accurately quantify anti-rabies glycoprotein antibodies in serum of several animal species. In this method, purified rabies virus-like particles (VLPs) are used as antigen to coat the plates, while the presence of specific rabies immunoglobulins is revealed through blocking the recognition of these VLPs by a biotinylated monoclonal antibody. A quality by design approach was carried out in order to optimize the method performance, improving the sensitivity and, thereby, reducing the limit of detection of this assay. After the method validation, we confirmed that the bELISA method is able to detect a concentration of 0.06 IU/mL rabies immunoglobulins, titer lower than the 0.5 IU/mL cutoff value established as indication for correct vaccination. Further, we assessed the correlation between bELISA, the MNT, and the Platelia methods, confirming the accuracy of this new assay. On the other hand, precision was evaluated, obtaining acceptable repeatability and intermediate precision values, showing that this bELISA could be proposed as a potential alternative method, replacing the gold standard techniques in vaccination schemes and becoming a routine control technique within regional rabies surveillance programs.

Step-wise approach to developing a scale-independent design space for functional tablet coating process.

The objective of this study is to present a practical example of a scale-independent design space development using a step-wise approach. A detailed description of the development process with a systematic outline of the main steps is provided. Design space is developed for film coating of tablets with moisture protective polyvinyl alcohol (PVA) based coating. The impact of scale-independent coating process parameters on the properties of film-coated tablets (FCT), i.e. water activity and film coating protection ability, and consequently on product long-term stability is explored. The main finding is that with model simplifications, a step-wise approach and rational development of scale-independent design space for the coating process, it is possible to efficiently predict, control, and optimize the long-term stability of a moisture sensitive product. However, the PVA moisture protective coating itself is recognized as having conflicting effects on product stability.

Optimization of the Microwave Assisted Glycosylamines Synthesis Based on a Statistical Design of Experiments Approach.

Glycans carry a vast range of functions in nature. Utilizing their properties and functions in form of polymers, coatings or glycan derivatives for various applications makes the synthesis of modified glycans crucial. Since amines are easy to modify for subsequent reactions, we investigated regioselective amination conditions of different saccharides. Amination reactions were performed according to Kochetkov and Likhoshertov and accelerated by microwave irradiation. We optimized the synthesis of glycosylamines for N-acetyl-d-galactosamine, d-lactose, d-glucuronic acid and l-(-)-fucose using the design of experiments (DoE) approach. DoE enables efficient optimization with limited number of experimental data. A DoE software generated a set of experiments where reaction temperature, concentration of carbohydrate, nature of aminating agent and solvent were investigated. We found that the synthesis of glycosylamines significantly depends on the nature of the carbohydrate and on the reaction temperature. There is strong indication that high temperatures are favored for the amination reaction.

A Comparison Between Lab-Scale and Hot-Melt-Extruder-Based Anti-inflammatory Ointment Manufacturing.

Hot-melt extrusion (HME) has been extensively investigated for continuous manufacturing of amorphous solid dispersions, to improve the solubility of poorly water-soluble drug substances, impart abuse deterrence to controlled substances, taste masking for pediatric and geriatric formulations and development of cocrystal system. Much research has been conducted on the continuous manufacturing of solid dosage forms using HME, but its applicability in the manufacturing of semisolids remains an unexplored domain. This study aimed to explore the applicability of HME in the continuous manufacturing of topical semi-solid formulations with two active pharmaceutical ingredients (APIs). Ointments containing a combination of triamcinolone acetonide and lidocaine hydrochloride were screened based on a quality target product profile (QTPP) and established critical quality attributes (CQAs) using design of experiments (DoE). Three selected formulations, manufactured by a lab-scale fusion method and HME, were subjected to further characterization studies including work of adhesion, stiffness, apparent pH, content uniformity, differential scanning calorimetry, accelerated stability, and in vitro drug release testing. Selected formulations met design characteristics and demonstrated the applicability of HME in the continuous manufacturing of semi-solid formulations. Graphical abstract.

Simultaneous detection of nicotinamide adenine nucleotides and adenylate pool to quantify redox and energy states in mAb-producing CHO cells by capillary electrophoresis.

Chinese hamster ovary (CHO) cells are predominant in the production of therapeutic proteins to treat various diseases. Characterization and investigation of CHO cell metabolism in a quick and simple way could boost process and cell line development. Therefore, a method to simultaneously detect seven redox- and energy-related metabolites in CHO cells by capillary electrophoresis has been developed. An on-line focusing technique was applied to improve the peak shape and resolution by using a 50 µm × 44 cm uncoated fused silica capillary. Key parameters and their interactions were investigated by design of experiments (DoE) and optimized conditions were determined by desirability function as follows: 24 °C, 95 mM, and pH 9.4 of BGE. The method was validated to ensure sensitivity, linearity, and reproducibility. The limits of detection (LODs) ranged from 0.050 to 0.688 mg/L for seven metabolites, and correlation coefficients of linearity were all greater than 0.996. The relative standard deviations (RSD) of migration time and peak area were smaller than 0.872% and 5.5%, respectively, except for NADPH, and the recoveries were between 97.5 and 101.2%. The method was successfully applied to analyze the extracts from CHO cells under two different culture conditions. Graphical abstract.