ABSTRACT The co-production of melanin during Aureobasidium pullulans fermentation compromises the purity and functionality of pullulan. To address this, acid-activated date seed biochar was evaluated for the selective removal of melanin from crude pullulan. A central composite design of experiment was adopted to vary solution pH, contact time (CT), and biochar concentration (BC) in the batch adsorption process, while quantifying melanin and pullulan recovery through a rapid, nondestructive chemometric Partial Least Square Regression (PLSR) model (R2 CV 0.99) built on designed blends. Hyperparameter-optimized Artificial Neural Network (ANN) models trained on Gaussian noise-augmented data demonstrated excellent prediction performance for both melanin adsorption (R2: 0.97, R2 CV: 0.95) and polymer loss (R2: 0.99, R2 CV: 0.99). Explainable machine learning tools, such as Shapley Additive Explanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME), were used to interpret the developed ANN models. Genetic algorithm-based multi-objective optimization suggests melanin removal of 87.56% and polymer loss of 14.55% under optimal biosorption conditions (i.e. pH: 5.16, CT: 36.59 min, and BC: 20.00 g L−1), closely matching the observed melanin removal (86.85%), polymer loss (17.42%) in the validation run. Combining green adsorbents, chemometric tools, and a machine learning model provides a robust, scalable solution for downstream processing of biopolymers.

Background/Objectives: Manual preparation of semisolid formulations (creams, ointments, gels) is prone to variability in mixing energy and time, which may compromise uniform API distribution. This study aimed to evaluate an Electronic Mortar and Pestle (EMP; Unguator™) as a standardized compounding tool, with objectives to: (i) validate stability-indicating UHPLC methods; (ii) assess content uniformity across jar strata; (iii) quantify the impact of mixing time and rotation speed via design of experiments (DOE); and (iv) verify cleaning effectiveness and cross-contamination risk. Methods: Five representative formulations were compounded: urea 40%, clobetasol 0.05%, diclofenac 2.5% in hyaluronic acid 3% gel, urea 10% + salicylic acid 1%, and hydroquinone 5%. UHPLC methods were validated per ICH Q2(R2) and stress-tested under acid, base, oxidative, thermal, and UV conditions. Homogeneity was assessed by stratified sampling (top/middle/bottom). A 32 factorial DOE (time: 2/6/10 min; speed: 600/1500/2400 rpm) modeled effects on % label claim and RSD. Cleaning validation employed hydroquinone as a tracer, with swab sampling pre-/post-use and post-sanitization analyzed by HPLC. Results: All UHPLC methods met specificity, linearity, precision, accuracy, and sensitivity criteria and were stability-indicating (Rs ≥ 1.5). Formulations achieved 90–110% label claim with strata CV ≤ 5%. DOE revealed speed as the dominant factor for clobetasol, urea, and diclofenac, while time was more influential for salicylic acid; gels exhibited curvature, indicating diminishing returns at high rpm. Model-predicted optima were implementable on the Unguator™ with minor rounding of rpm/time. Cleaning validation confirmed post-sanitization residues below LOQ and <10 ppm acceptance. Conclusions: The Unguator™ provides a practical, parameter-controlled route for compounding pharmacies to standardize semisolid preparations, achieving reproducible layer-to-layer content uniformity within predefined criteria under the evaluated conditions through programmable set-points and validated cycles. DOE-derived rpm–time relationships define an operational design space within the studied ranges and support selection of implementable device settings and set-points. Importantly, the DOE-derived “optima” in this study are optimized for assay-based content uniformity (mean % label claim and strata variability). Cleaning validation supports a closed, low-cross-contamination workflow, facilitating consistent routines for both routine and complex formulations. Overall, the work implements selected QbD elements (QTPP—Quality Target Product Profile; CQA—Critical Quality Attribute definition; CPP—Critical Process Parameter identification; operational design space; and a proposed control strategy) and should be viewed as a step toward broader lifecycle QbD implementation in compounding.

Particle size, shape and distribution of an active pharmaceutical ingredient (API) can significantly influence the physicochemical and biopharmaceutical performance of dosage forms. However, development of particle size analytical methods for APIs/formulation with diverse particle characteristics remains challenging. Only a limited number of studies have reported a Quality by Design (QbD) based framework for developing laser diffraction particle size methods beyond conventional trial-and-error approaches. This study aimed to establish a structured, science-driven and risk-based QbD approach for the development and validation of a laser diffraction analytical method for determining the particle size distribution (PSD) of Dapagliflozin Propanediol. The work highlights the application of Analytical Quality by Design (AQbD) principles including predefined objectives, systematic process understanding and effective control of analytical variability to ensure method robustness, reliability and regulatory compliance. Prior knowledge of the API and drug product was used to construct an Ishikawa (cause-and-effect) diagram and to support Failure Mode and Effects Analysis (FMEA) for analytical risk assessment. An Analytical Target Profile (ATP) was defined to ensure accurate and precise determination of Dv10, Dv50, and Dv90 values within predefined acceptance criteria (Dv10 ≤ 15%, Dv50 ≤ 10%, and Dv90 ≤ 15%). Dispersant type, sonication time, stirrer speed and percentage obscuration were identified as critical method parameters. A Design of Experiments (DoE) strategy was employed to optimize these parameters within defined operational ranges using Fusion QbD software (version 9.9.2 SR3) and a face-centered central composite design (FCCCD). Method development followed ICH Q8–Q10 and ICH Q14 guidelines, while validation was conducted in accordance with ICH Q2 and EP 2.9.31/USP <429>. The optimized method demonstrated excellent precision and reproducibility with repeatability values of 9.96% (Dv10), 5.01% (Dv50), and 11.56% (Dv90). Overall, the QbD-based approach provided enhanced method understanding and control, resulting in a robust and reliable analytical procedure for particle size characterization of Dapagliflozin Propanediol.

Cardiopulmonary bypass (CPB) is a well-established procedure that uses cannulae during cardiac surgery to drain and return blood. In challenging cases (e.g. aortic dissection, reoperation), peripheral cannulation in vessels such as the axillary artery are used. However, standard cannulae at these sites may inhibit blood flow to distal extremities or require grafts that increase surgical time. This study evaluates a novel, flexible-tip arterial cannula designed for bi-directional flow. A 22Fr body cannula was developed to achieve a pressure loss (ΔP) < 100mmHg and 80/20 bi-directional flow distribution between tip outlets. A full factorial design of experiments (2-levels, 4 factors: tip A-width, B-height, C-depth, D-outlet shape) was completed to evaluate sixteen cannula tip designs using benchtop hydraulic and bi-directional flow models. Prototypes were fabricated using 3D printing via stereolithography (Form 3 + , Formlabs, Somerville, MA) with a flexible (50A) cured resin. The most efficient cannula design (A - , B + , C + , D + ) achieved 4 L/min of total bi-directional flow at a ΔP of 74mmHg. The average ΔP at 4 L/min for all candidate design was 87 ± 9mmHg (range 72-100mmHg). Primary outlet flow distribution averaged 81% ± 6% (range 70-95%) at 1-5 L/min flow rates. Tip width had the greatest influence on ΔP, followed by outlet shape, depth, and their interactions, respectively. Cylindrical and prolate spheroid shaped tips outperformed spherical designs. The novel cannula demonstrated feasibility and proof-of-concept as evidenced by bi-directional flow with ΔP comparable to commercial cannulae. Future work will involve CFD modeling and pre-clinical validation (e.g. hemolysis, cadaver fit) to support development of a low-cost, clinical grade bi-directional flow cannula for peripheral CPB to reduce surgical complexity and lower risk of adverse events.

The potential for biomass as an alternative source of energy is being studied widely. In this study, process flow design is done to analyse the pyrolysis of biomass and its products and how energy can be generated from its products. The energy used per process is calculated and the heat required in the processes were also calculated. The optimization of process parameters for the production of energy from wood biomass via pyrolysis was conducted using the Response Surface Methodology (RS) in the Design Expert 2022 environment using the following range of process parameters: temperature (400-1000°C), vapour residence time (5-30 min) and particle size (0.5-2.0 mm). The feasible combination of process parameters from the design of experiment was validated via physical experimentation having three responses namely: yield of char, yield of biofuel and yield of syngas. The designed experiments and corresponding outcomes produced three predictive models for estimating the yields of char, biofuel and syngas as a function of temperature, vapour residence time and particle size. The results obtained indicated that low temperature favours the formation of biochar while moderate temperature favours the formation of biofuel and the production of syngas is favoured by elevated temperature. The optimal values of process parameters and responses obtained include: temperature (642.271 °C), vapour residence time (6.248 min), particle size (0.603 mm), yield of char (71.9%), yield of biofuel (71.9%) and yield of syngas (76.5%). This study adds to the literature on the pyrolysis process for the conversion of wood biomass to energy. It also contributes to the fields of renewable and sustainable energy generation. Keywords: Biomass, biofuel, char, renewable and sustainable energy, RSM, syngas

Antibody-drug conjugates (ADCs) are a promising and emerging class of biotherapeutics that combine the targeting precision of monoclonal antibodies (mAbs) with the cytotoxic potency of small-molecule drugs. Their manufacturing, however, requires conjugation of the mAb with the pertinent small molecule drug, a step typically is inefficient, incurring wastage of both the mAb and the drug. In addition, ADC manufacturing is challenged by precise control of drug-to-antibody ratio (DAR), aggregation, safe handling of cytotoxic payloads, among other factors. In this work, we present a novel approach for continuous conjugation of the mAb and the drug, by utilizing a coiled flow inverter reactor (CFIR) to facilitate the thiol-maleimide conjugation at interchain cysteines residues in the mAb. As an initial step, the process parameters for reducing thiol groups and the conjugation steps were screened, followed by optimization of the significant parameters (concentration of mAb and drug/linker payload, reaction duration, and temperature) using design of experiments (DoE) methodology. The performance of the CFIR was then compared to that of traditional batch conjugation. We demonstrate that the CFIR offers 64.40% higher productivity, 70% lower cost of production, and a safer alternative to the traditional batch conjugation, while producing clinically relevant DAR. This work illustrates the potential of continuous processing to transform ADC manufacturing by enabling more efficient, scalable, and sustainable production platforms.

A sensitive, selective, and robust ultra-high-performance liquid chromatography method was developed for the simultaneous quantification of anastrozole and five process-related impurities at trace levels (≤ 0.1%). Traditional univariate optimization was replaced with a systematic chemometric approach using Box-Behnken Design to evaluate critical chromatographic parameters-mobile phase pH (3.0-4.0), column temperature (25°C-35°C), and flow rate (0.20-0.60 mL/min). Response Surface Methodology was employed to model retention behavior, resolution, and peak symmetry, with desirability function optimization identifying the ideal conditions (pH 3.20, 29.3°C, 0.33 mL/min). The method achieved baseline separation on an ACQUITY BEH C18 column (2.1 × 50 mm, 1.7 μm) using 10-mM ammonium formate (pH-adjusted) and acetonitrile as the mobile phase. Validation per International Council for Harmonisation Q2(R1) guidelines confirmed excellent linearity (R2 ≥ 0.999), precision (%RSD ≤ 1.5% for ANZ; ≤ 5.3% for impurities), accuracy (recoveries: 94%-101%), and sensitivity (limit of detection: 0.011-0.014 μg/mL; limit of quantitation: 0.020-0.025 μg/mL). This study reports the first validated ultra-high-performance liquid chromatography method enabling trace-level quantification of two newly identified (IMP-1 and IMP-2) and three previously reported process-related impurities of anastrozole in a single run, using a Design of Experiments-based optimization approach.

Smart culture medium optimization for recombinant protein production: Experimental, modeling, and AI/ML-driven strategies.

Dataset of numerical assessment on the combined effects of non-thermal plasma and water addition in hydrogen combustion.

The commercialization of aqueous zinc‐ion batteries (ZIBs) remains hindered by poor Zn electrodeposition efficiency in mild‐acidic electrolytes, mainly due to the parasitic hydrogen evolution reaction (HER). The use of metallic substrates, such as copper or indium, has proven to be one of the most effective and potentially industrially viable strategies for kinetically promoting zinc electrodeposition over hydrogen evolution, while simultaneously ensuring a uniform deposit morphology. Here, a scalable strategy to fabricate indium‐containing substrates via galvanic displacement, offering a simple, cost‐effective, and environmentally sustainable alternative to conventional production methods has been presented. The prepared substrates demonstrate average efficiencies exceeding 99% over 150 Zn stripping/plating cycles at a realistic depth of discharge, requiring a fraction of Zn reservoir compared to standard Zn electrodes. A multivariate design of experiment (DOE) approach is employed to optimize both electrode fabrication and electrolyte parameters, highlighting key variables affecting Zn deposition efficiency and uncovering critical synergistic and antagonistic effects otherwise hidden in traditional one‐variable‐at‐a‐time (OVAT) methods. Overall, this work not only demonstrates the feasibility of upscaling indium‐modified substrates for high‐performance ZIBs but also emphasizes the power of DOE in accelerating material optimization and deepening the understanding of complex electrochemical systems.

ABSTRACT Equivalent series resistance (ESR) is a critical factor limiting the performance and longevity of asymmetric supercapacitors (ASCs). Failed ASC analysis shows ESR imbalance as a major cause of degradation. This study uses statistical design of experiment (DoE) models for vertical and horizontal setups to tightly control ESR. A high coefficient of determination value confirms the validity of the model over a significant data variance. Accurate electrode loading control influences ESR variance more than metal oxide content, though their interaction also significantly affects ESR. With precise loading, ESR remains within a narrow, stable range across configurations. Controlled ESR directly influences the design and cost of cell balancing circuits. The study identifies better alternatives to metal oxides and activated carbon for enhanced performance. Finally, COMSOL thermal simulations show asymmetric cooling is a key for ASC performance and reliability.

Optimization of rabies virus production in neuroblastoma cells using quality by design principles for vaccine and diagnostic applications.

Preliminary evaluation of Design of Experiments (DoE) approach for the performance prediction of basalt sawing sludge- metakaolin-based Alkali Activated Materials (AAMs)

From materials to management: The expanding role of design of experiments in advanced battery technologies

One-step formation of plasmid DNA-loaded lipid-inorganic salt nanoparticles optimized via two-step design of experiments.

In this study, a numerical approach was adopted to optimize the geometric parameters of the patch and adhesive to improve the repair performance of a carbon/epoxy laminated composite structure. The studied laminate has a stacking sequence of [45/0/-45/90]s, representative of configurations commonly used in engineering. The analysis was performed using a three-dimensional nonlinear finite element method (FEM), applied to a notched composite plate subjected to tensile loading and repaired with a circular patch of the same material, placed on both sides. The existing literature focuses mainly on the separate evaluation of geometric or mechanical parameters, while the analysis of their interactions remains limited. Furthermore, the application of statistical methods such as design of experiments (DoE) for multi-parameter optimization of composite repairs remains marginal. It is in this context that the present study proposes a methodology integrating detailed 3D FEM modeling and multi-parameter analysis based on DoE, allowing the simultaneous evaluation of the influence of patch diameter, adhesive thickness, and shear modulus on the response of the repaired structure. The results show that mechanical strength increases with patch surface area, while excessive adhesive thickness reduces local stiffness. Among the parameters studied, the patch diameter is the dominant factor. The proposed approach is therefore a useful tool to improve the effectiveness and durability of bonded patch repairs.

The Np sphere is a 6070.4-g sphere of neptunium metal cast by Los Alamos National Laboratory in 2001. Neptunium is of interest to the nuclear community for applications such as space exploration and reactor fuel. The Np sphere is composed mostly of 237Np, which is a threshold fissioner. It requires an approximately 700-keV neutron to fission and therefore can go critical with only fast neutrons. The objective behind casting the sphere was to calculate the critical mass of neptunium and further understand neptunium nuclear data. This objective was partially met with critical benchmarks; however, an attempt to maximize sensitivity to 237Np led to the design and execution of a subcritical experiment. When analyzing data from this experiment, there were questions about the sphere’s composition, contaminant distribution, and hot spot location. This work begins by summarizing what is currently known about the fabrication and material composition of the sphere. Two material analyses have been completed on pieces of neptunium metal from the fabrication of the sphere that indicate the existence of 241Am, 243Am, and 244Cm. Thereafter, new neutron and gamma data revealed information about the hot spot distribution and its location. The hot spot, thought to be fixed at a mark made on the cladding during fabrication at the sprue location, now appears to move. Although lack of information and movement of the hot spot complicate its ability to be included in benchmark experiments, the need for additional neptunium nuclear data validation data still exists. The results detailed in this work will be vital in the design and planning of future Np sphere experiments.

Introduction. This article presents the development of a technology for obtaining lozenges containing Ajania fruticulosa dry extract using the direct compression method. The Quality by Design (QbD) concept reflects a modern approach to pharmaceutical development based on the identification and control of Critical Quality Attributes (CQA) and Critical Process Parameters (CPP) that determine their variability. The application of Design of Experiments (DoE) allows for the quantitative assessment of the influence of technological variables and their interactions, optimization of production conditions, reduction of experimental series volume, and ensuring the control of the technological process. Aim. To develop the composition and technology of lozenges with Ajania fruticulosa dry extract using the direct compression method and applying the principles of the QbD concept. Materials and methods. A standardized Ajania fruticulosa dry extract, obtained by maceration with ultrasonic intensification in accordance with the EAEU Pharmacopoeia, was used as the Active Pharmaceutical Ingredient (API). The lozenges were obtained by the direct compression method with varying concentrations of talc (0.1–3.0 %), copovidone (2.0–5.0 %), and compression pressure (15–30 kN). Disintegration time and friability were chosen as the CQAs. Experimental design and statistical analysis were performed using Minitab Statistical Software 22.3.0 (LLC "Minitab", USA) with the DoE module. Disintegration time and friability were determined in accordance with the requirements of the EAEU Pharmacopoeia using ZT 320 and TAR 220 apparatuses (ERWEKA GmbH, Germany). Results and discussion. The optimal API concentration was 1.5 %. According to the DoE results, the copovidone content and compression pressure had a statistically significant effect on the disintegration time, while the contribution of talc was insignificant. The optimal parameters were: copovidone – 5 %, talc – 2 %, compression force – 22 kN. Under these conditions, the disintegration time was 12.9 min, friability was 0.50 %, and the overall desirability index D = 0.8168. Conclusion. The implementation of the QbD concept in combination with DoE provided a scientifically grounded approach to the development of lozenges with Ajania fruticulosa dry extract. The developed lozenges meet the requirements of the EAEU Pharmacopoeia and are recommended for scale-up and industrial production.

Morphological models offer significant improvements over static vertebral models by providing predictive capabilities for personalized medicine and injury prevention. These models are invaluable for evaluating biomechanical implications of surgical outcomes and designing personalized rehabilitation plans. Traditional in vitro experiments are limited by the minimal shape variation in available populations. This study aims to assess the sensitivity of anthropometric features on the biomechanical responses of the L4-L5 lumbar functional spine unit (FSU) under moment loading conditions. A population of L4-L5 FSUs was generated using a Design of Experiment (DoE) framework. One Factor at a Time (OFAT) analysis at five levels and Constrained Lattice Hyper Cube Sampling (CLHS) with 200 samples were employed. Anthropometric variations in disc wedging angle, anteroposterior diameter, transverse diameter (TD), vertebral height, and facet sagittal angle were applied using ANSA BETA CAETM. Morphing operations ensured anatomical adaptability without compromising mesh quality. Sensitivity analysis was performed using Pearson's Correlation Coefficient to evaluate the relationship between anthropometric parameters and biomechanical responses, including range of motion, disc pressures, and facet contact forces (CF). Model responses were validated against in vitro experimental data to confirm biomechanical fidelity. Sensitivity analysis using linear regression coefficients identified transverse diameter (-0.99 against range of motion (ROM)), anteroposterior diameter (-0.97 against ROM), and disc wedging angle (0.90 against facet contact force) as the most influential input parameters across different loading scenarios. The Pearson correlation analysis further substantiated these findings, revealing strong linear associations between morphological variations and biomechanical responses. These trends exhibited good agreement with existing in vitro experimental data. This study highlights the importance of geometric variations in determining biomechanical responses of the L4-L5 FSU. The findings provide a framework for treatment planning, critical response prediction, and patient-specific surgical outcome evaluation, paving the way for advancements in personalized medicine and rehabilitation.

The integrated of bio-based and sustainable composite materials had advanced the additive manufacturing (AM) industry, particularly for fused deposition modelling (FDM). Natural fibre-reinforced composites are gaining prominence due to their eco-friendly properties and compatibility with thermoplastics. This study investigates the influence of infill density and layer thickness on the mechanical properties of a novel pineapple leaf fibre (PALF)reinforced poly-lactic acid (PLA) composite filament used for 3D printing. The composite filament was fabricated through a structured process involving fibre crushing, sieving, mixing with PLA matrix and extrusion. To study the effects of infill density and layer thickness, a series of tensile and flexural test specimens were fabricated in accordance with ASTM D638 and D790 standards, respectively. A design of experiments (DoE) approach, specifically the Taguchi method, was employed to systematically evaluate the influence of layer thickness (0.1 mm, 0.2 mm, 0.3 mm), printing speed (25 mm/s, 50 mm/s, 100 mm/s) and infill density (25%, 50%, 100%), on the mechanical performance. The results revealed a significant correlation between the chosen FDM parameters and the mechanical properties of the PALF/PLA composite. Higher infill density generally contributed to improved tensile and flexural strength due to increased internal material support and reduced void formation. Conversely, lower infill densities, while reducing material consumption and printing time, exhibited reduced mechanical strength. Layer thickness also demonstrated the least influence on the mechanical properties. However, increased layer thickness reduced build time and material overlap. The interaction between infill density and tensile performance is also confirmed in this study with the score of r꞊0.9799 and r꞊0.9806. Negative effect between the printing speed and all mechanical properties with the range values between r꞊-0.0569 and r꞊-0.3608. The study concludes that optimizing these parameters is essential to balance mechanical strength, material efficiency, and printing time. This research contributes to the growing body of knowledge on sustainable 3D printing materials and provides practical insights for optimizing process parameters when using natural fibre composites. It highlights the potential of pineapple leaf fibre as a valuable reinforcement in biodegradable thermoplastics, promoting a circular economy and sustainable manufacturing practices.