Design Of Experiments Research Articles

Optimizing Carbon Structures in Laser-Induced Graphene Electrodes Using Design of Experiments for Enhanced Electrochemical Sensing Characteristics.

In this study, we explored the morphological and electrochemical properties of carbon-based electrodes derived from laser-induced graphene (LIG) and compared them to commercially available graphene-sheet screen-printed electrodes (GS-SPEs). By optimizing the laser parameters (average laser power, speed, and focus) using a design of experiments response surface (DoE-RS) approach, binder-free LIG electrodes were achieved in a single-step process. Traditional trial-and-error methods can be time-consuming and may not capture the interactions between all variables effectively. To address this, we focused on linear resistance and substrate delamination to streamline the DoE-RS optimization process. Two LIGs, designated LIG A and LIG B, were fabricated using distinct and optimized laser settings, which resulted in a sheet resistance of 25 ± 2 Ω/sq and 21 ± 1 Ω/sq, respectively. These LIGs, characterized by scanning electron microscopy, Raman spectroscopy, and contact angle analysis, exhibited a highly porous morphology with 13% pore coverage and a contact angle <50°, which significantly increased their hydrophilicity when compared to the GS-SPE. For the electrochemical studies, the oxidation of NO2- ion by the graphene-based working electrodes was investigated, as it allowed for the direct comparison of the LIGs to the GS-SPE. These included cyclic voltammetry, electrochemical impedance spectroscopy, and differential pulsed voltammetry studies, which revealed that LIG electrodes displayed a remarkable 500% increase in peak current during NO2- oxidation compared to the GS-SPE. The LIGs also demonstrated improved stability and sensitivity (420 ± 30 and 570 ± 10 nAμM-1 cm-2) compared to the GS-SPE (73 ± 4 nAμM-1 cm-2) in the oxidation of NO2- ions; however, LIG B was more susceptible to ionic interference than LIG A. These findings highlight the value of applying statistical approaches such as DoE-RS to systematically improve the LIG fabrication process, enabling the rapid production of optimized LIGs that outperform conventional carbon-based electrodes.

Pathophysiology and preclinical relevance of experimental graft-versus-host disease in humanized mice.

Graft-versus-host disease (GVHD) is a life-threatening complication of allogeneic hematopoietic cell transplantations (allo-HCT) used for the treatment of hematological malignancies and other blood-related disorders. Until recently, the discovery of actionable molecular targets to treat GVHD and their preclinical testing was almost exclusively based on modeling allo-HCT in mice by transplanting bone marrow and splenocytes from donor mice into MHC-mismatched recipient animals. However, due to fundamental differences between human and mouse immunology, the translation of these molecular targets into the clinic can be limited. Therefore, humanized mouse models of GVHD were developed to circumvent this limitation. In these models, following the transplantation of human peripheral blood mononuclear cells (PBMCs) into immunodeficient mice, T cells recognize and attack mouse organs, inducing GVHD. Thereby, humanized mice provide a platform for the evaluation of the effects of candidate therapies on GVHD mediated by human immune cells in vivo. Understanding the pathophysiology of this xenogeneic GVHD is therefore crucial for the design and interpretation of experiments performed with this model. In this article, we comprehensively review the cellular and molecular mechanisms governing GVHD in the most commonly used model of xenogeneic GVHD: PBMC-engrafted NOD/LtSz-PrkdcscidIL2rγtm1Wjl (NSG) mice. By re-analyzing public sequencing data, we also show that the clonal expansion and the transcriptional program of T cells in humanized mice closely reflect those in humans. Finally, we highlight the strengths and limitations of this model, as well as arguments in favor of its biological relevance for studying T-cell reactions against healthy tissues or cancer cells.

Optimization of Laser Based-Powder Bed Fusion Parameters for Controlled Porosity in Titanium Alloy Components

Laser based-powder bed fusion (LB-PBF) enables fast, efficient, and cost-effective production of high-performing products. While advanced functionalities are often derived from geometric complexity, the capability to tailor material properties also offers significant opportunities for technical innovation across many fields. This study explores the optimization of the LB-PBF process parameters for producing Ti6Al4V titanium alloy parts with controlled porosity. To this end, cuboid and lamellar samples were fabricated by systematically varying laser power, hatch distance, and layer thickness according to a full factorial Design of Experiments, and the resulting specimens were thoroughly characterized by analyzing envelope porosity, surface roughness and waviness, surface morphology, and surface area. A selection of specimens was further examined using small-angle X-ray scattering (SAXS) and wide-angle X-ray scattering (WAXS) to investigate the atomic structure and nanometric porosity of the material. The results demonstrated the possibility to finely control the porosity and surface characteristics of Ti6Al4V within specific LB-PBF process ranges. The pores were found to be mostly closed even for thin walls, while the surface roughness was recognized as the primary factor impacting the surface area. The lamellar samples obtained by exposing single scan tracks showed nearly an order-of-magnitude increase in both surface area and pore volume, thereby laying the groundwork for the production of parts with optimized porosity.

THE EFFECT OF DEGREASING TEMPERATURE ON THE THICKNESS OF THE FORMED LAYER CREATED BY CATAPHORETIC PAINTING

The article investigates the impact of degreasing temperature in the degreasing mixture PRAGOLOD 57N on cataphoretic painting using design of experiments (DoE). Key technological factors such as degreasing deposition time, concentration, cataphoretic deposition time, and voltage are examined for their effect on the thickness of the formed anti-corrosion layer. Cataphoretic painting, an economical and eco-friendly method, is widely used for treating metal parts in automotive and engineering industries. The study involves testing 88 samples, with thickness measurements taken via Elcometer 456C according to the ISO standards and graphical analysis performed using statistical software to optimize the process.

Optimizing processes and products: The role of DOE

The Design of Experiment (DOE) methodology is a fundamental tool for systematic inquiry and optimization in both scientific and industrial applications. The DOE’s statistical framework is designed to enhance the efficiency and reliability of experimental investigations by systematically planning, conducting, and evaluating controlled experiments. To support well-informed decision-making, process optimization, and quality improvement, the main goal of DOE is to discover and quantify the effects of various variables on a response variable. Various methods such as full factorial, fractional factorial, Taguchi, and response surface methodologies provide powerful tools for optimising processes and enhancing quality. The study covers the application of DOE in several industries, including engineering, manufacturing, agriculture, and medicine. Defect minimization, process optimization, and quality improvement are all aided by DOE in manufacturing. By determining the best dosages and formulations, it helps in drug development in the pharmaceutical industry. In the field of agriculture, DOE facilitates the identification of optimal growing conditions and techniques. It helps in the engineering and assessing new systems and products. To achieve consistency and accuracy in data collection, the experiment must be carried out with strict adherence to the experimental strategy. Analysing data involves using statistical tools to evaluate the findings and make conclusions, such as ANOVA, regression analysis, and graphical approaches. By pointing out important variables and their interactions, these studies aid in process optimization and product quality enhancement.

Damage indicators evolution during cyclic loading of composite plate with hole

Novel experimental method, which provides quantitative description of damage indicators evolution caused by fatigue loading of composite specimens with stress concentrators, was developed. Damage parameters are derived as deformation response to artificial notch inserting. This notch is extended from the edge of central through hole in plane rectangular specimen under constant external load. Current values of damage indicators are obtained at different stages of fatigue loading. These data reveal dependencies of required parameters on loading cycle number. The damage accumulation function for involved cycle range is quantitatively constructed on this base. It is found that this function is related to the first stage of the process investigated. The results obtained represent the essential link in the design of further experiments.

Validating the Influences of Methodological Decisions on Assessing the Spatiotemporal Stability of Speech Movement Sequences Using Children's Speech Data.

Prior research introduced quantifiable effects of three methodological parameters (number of repetitions, stimulus length, and parsing error) on the spatiotemporal index (STI) using simulated data. Critically, these parameters often vary across studies. In this study, we validate these effects, which were previously only demonstrated via simulation, using children's speech data. Kinematic data were collected from 30 typically developing children and 15 children with developmental language disorder, all spanning the ages of 6-8 years. All children repeated the sentence "buy Bobby a puppy" multiple times. Using these data, experiments were designed to mirror the previous simulated experiments as closely as possible to assess the effects of analytic decisions on the STI. Experiment 1 manipulated number of repetitions, Experiment 2 manipulated stimulus length (or the number of movement units in the target phrase), and Experiment 3 manipulated precision of parsing of the articulatory trajectories. The findings of all three experiments closely mirror those of the prior simulation. Experiment 1 showed consistent underestimation of STI values from smaller repetition counts consistent with the theoretical model for all three participant groups. Experiment 2 found speech segments containing fewer movements yield lower STI values than longer ones. Finally, Experiment 3 showed even small parsing errors are found to significantly increase measured STI values. The results of this study are consistent with the findings of prior simulations in showing that the number of repetitions, length of stimuli, and amount of parsing error can all strongly influence the STI independent of behavioral factors. These results further confirm the importance of closely considering the design of experiments, which employ the STI.

Model-Based Sequential Design of Experiments with Machine Learning for Aerospace Systems

Traditional experimental design methods often face challenges in handling complex aerospace systems due to the high dimensionality and nonlinear behavior of such systems, resulting in nonoptimal experimental designs. To address these challenges, machine learning techniques can be used to further increase the application areas of modern Bayesian Optimal Experimental Design (BOED) approaches, enhancing their efficiency and accuracy. The proposed method leverages neural networks as surrogate models to approximate the underlying physical processes, thereby reducing computational costs and allowing for full differentiability. Additionally, the use of reinforcement learning enables the optimization of sequential designs and essential real-time capability. Our framework is validated by optimizing experimental designs that are used for the efficient characterization of turbopumps for liquid propellant rocket engines. The reinforcement learning approach yields superior results in terms of the expected information gain related to a sequence of 15 experiments, exhibiting mean performance increases of 9.07% compared to random designs and 6.47% compared to state-of-the-art approaches. Therefore, the results demonstrate significant improvements in experimental efficiency and accuracy compared to conventional methods. This work provides a robust framework for the application of advanced BOED methods in aerospace testing, with implications for broader engineering applications.

Eccentric magnetic abrasive finishing of 316 steel

This paper presents a new method of eccentric magnetic-abrasive finishing as applied to 316 stainless steel. The proposed solution is based on solid ferromagnetic abrasive grains (Fe-Si) held by an external magnetic field. A workpiece fixed in a holder with a certain eccentricity is inserted between the grains and the holder is rotated. The use of an additional eccentricity has a significant impact on the nature of the process, in particular, it increases the speed of the sample relative to the abrasive grains, makes it possible to use more abrasive grains, induces mixing abrasive grains, which can prolong their active life time. In this study, a three-factor, five-level design of experiment was conducted. The variable parameters were: machining time, eccentric value, and rotational speed. Samples in the form of rollers with a diameter of 3 mm were mounted in a special holder that allowed to obtain the assumed eccentricity. Based on the results obtained, regression equations were developed for selected roughness parameters Ra, Rz, Rq, Rt. The value of Ra roughness decreased from the initial value of 0.575 μm to a value below 0.1 μm (an 80% decrease) in 9.1 min. The results obtained provided the basis for further research in conducting eccentricity in magnetic-abrasive machining as an intensifying element of the process.

Expanding the Analytical Toolbox for the Nondenaturing Analysis of siRNAs with Salt-Mediated Ion-Pair Reversed-Phase Liquid Chromatography.

Short interfering RNA (siRNA) represents a rapidly expanding class of marketed oligonucleotide therapeutics. Due to its double-stranded nature, the characterization of siRNA is twofold: (i) at the single-strand (denaturing) level for impurity profiling and (ii) at the intact (nondenaturing) level to confirm duplex formation and quantify excess single strands (including single strand-derived impurities). While denaturing analysis can be carried out using conventional ion-pair reversed-phase liquid chromatography (IP-RPLC), nondenaturing characterization of siRNA is a significantly less straightforward task. Typical IP-RPLC conditions have an intrinsic denaturing effect on siRNA, thereby limiting the development of viable approaches for the intact duplex analysis. In this study, we demonstrate, through the design of experiments of siRNA melting temperatures and chromatography analyses, that the simple addition of salts, such as phosphate-buffered saline and ammonium acetate, to eluents enhances the suitability of IP-RPLC for the nondenaturing analysis of siRNA during both UV- and mass spectrometry-based analysis. This work represents a milestone in overcoming the challenges associated with nondenaturing analysis of siRNAs by IP-RPLC and offers a fresh angle for exploring IP-RPLC of siRNAs.

Advanced HPTLC Method Development for Silibinin Analysis in Nanoformulated Scaffolds: A Box-Behnken Approach.

Silibinin (silybin), a bioactive component derived from the seeds of milk thistle (Silybum marianum), is recognized for its diverse pharmacological properties, including antioxidant, anti-inflammatory, and hepatoprotective effects. Given its therapeutic significance, accurately quantifying silybin in various formulations is essential. High-performance thin-layer chromatography (HPTLC) is a powerful analytical technique frequently used for this purpose. In this study, an HPTLC method was validated according to the International Council for Harmonization (ICH) guidelines to determine the concentration of silybin. The design of experiments (DoE), specifically the Box-Behnken design, was employed to optimize and understand the influence of critical method variables. The HPTLC method validation was performed using silica gel F254 HPTLC plates. The variables investigated included the composition of the mobile phase (% v/v), saturation time (minutes), and temperature in degree Celsius (°C), with the Box-Behnken design for optimization. The mobile phase consisted of chloroform, acetone, and formic acid in a 7:2:1 (v/v) ratio. Both the formulated scaffold and standard drug were applied to the plates, which were then processed in a twin chamber. After development, the plates were scanned at 288 nm using the Camag TLC Scanner IV with Vision CATS software. The validated HPTLC method demonstrated a strong linear relationship within the silybin concentration range of 2-10 μg/mL. The limit of detection (LOD) and limit of quantification (LOQ) for silybin were determined to be 0.469 and 1.423 μg/mL, respectively. Recovery studies indicated that the method provided accurate quantification, with recovery rates ranging from 97.53% to 99.82%. These results confirm the method's high accuracy, outstanding linearity, and reliability for the quantification of silybin in formulations. The validated HPTLC method proved to be a reliable analytical tool for the quantification of silybin in various formulations, particularly those containing polymers. The method's strong linearity, precision, and accuracy align with the ICH guidelines, making it suitable for routine analysis in quality control laboratories. The use of the Box-Behnken design for method optimization highlights the importance of systematic experimentation in achieving robust analytical outcomes.

Identifying and optimizing critical process parameters for large-scale manufacturing of iPSC derived insulin-producing β-cells

BackgroundType 1 diabetes, an autoimmune disorder leading to the destruction of pancreatic β-cells, requires lifelong insulin therapy. Islet transplantation offers a promising solution but faces challenges such as limited availability and the need for immunosuppression. Induced pluripotent stem cells (iPSCs) provide a potential alternative source of functional β-cells and have the capability for large-scale production. However, current differentiation protocols, predominantly conducted in hybrid or 2D settings, lack scalability and optimal conditions for suspension culture.MethodsWe examined a range of bioreactor scaleup process parameters and quality target product profiles that might affect the differentiation process. This investigation was conducted using an optimized High Dimensional Design of Experiments (HD-DoE) protocol designed for scalability and implemented in 0.5L (PBS-0.5 Mini) vertical wheel bioreactors.ResultsA three stage suspension manufacturing process is developed, transitioning from adherent to suspension culture, with TB2 media supporting iPSC growth during scaling. Stage-wise optimization approaches and extended differentiation times are used to enhance marker expression and maturation of iPSC-derived islet-like clusters. Continuous bioreactor runs were used to study nutrient and growth limitations and impact on differentiation. The continuous bioreactors were compared to a Control media change bioreactor showing metabolic shifts and a more β-cell-like differentiation profile. Cryopreserved aggregates harvested from the runs were recovered and showed maintenance of viability and insulin secretion capacity post-recovery, indicating their potential for storage and future transplantation therapies.ConclusionThis study demonstrated that stage time increase and limited media replenishing with lactate accumulation can increase the differentiation capacity of insulin producing cells cultured in a large-scale suspension environment.

3D Printed Stent from Graphene-Polyethylene Glycol Diacrylate Using Digital Light Processing Technique

Abstract This paper presents the development of the photocurable resin material based on the graphene reinforced polyethylene glycol diacrylate (gPEGDA) for vascular stent fabrication using a commercial 3D printer. 3D printing with digital light processing (DLP) technique is an attractive alternative for low-cost fast fabrication with high accuracy. Four photocurable resin compositions were prepared by mixing PEGDA and varied composition of graphene and the photoinitiator according to the design of experiment of 22 full factorial design. The diphenyl (2,4,6-trimethylbenzoyl) phosphine oxide (TPO) photoinitiator was adopted to meet the required 405 nm UV-light source wavelength of the 3D printer for stent fabrication. Material characterization of the UV-absorbance and viscosity tests were conducted and optimized to obtain resin printability. Mechanical characteristics tests were conducted to obtain the best resin composition for stent application. For this purpose, the tensile tests were conducted according to the ASTM D638 standard using the type-V specimen size. The test specimens were 3D printed with varied UV exposure time 20 and 30 seconds. Finally, the stents were successfully fabricated using a commercial 3D printer DLP with the bottom parameter time setting of 60 seconds, and the UV exposure time of 30 seconds. The resin material was applicable for 3D printing of the stent. The result has shown that 3D printer with DLP technique is suitable for stent fabrication with excellent surface quality. Moreover, the innovative bioresorbable stent materials and fabrication approach could open up new possibilities in the development of medical devices, particularly in the treatment of vascular diseases.

Effect of Sporosarcina Pasteurii on Rheological and Strength Properties of Bio-Self Compacting Concrete

The study was conducted to evaluate the rheological and strength properties of bio-self compacting concrete. The materials used are cement, fine and coarse aggregates, bacteria (Sporosarcina pasteurii), and superplasticizer. Preliminary tests were conducted on the materials to ascertain its conformity to standard, and a full factorial design of experiment was adopted. The bacteria nutrient was varied at a ratio 1:3 of the bacteria content (i.e. 75% nutrient and 25% bacteria) at 10^5 cell/ml Sporosarcina pasteurii which was added to the fresh concrete at 5-25ml dosage by weight of water at 5ml increment, while the superplasticizer was added into the fresh concrete at 0.2-1.0% at 0.2 % increment by weight of cement which translated to 234 concrete samples. The rheological tests conducted were slump, V-funnel, L-box, and J-ring test, while the concrete strength tests conducted were compressive, flexural, and split tensile strength. Results from the experiment showed that workability of most of the bio-self compacting concrete is very high compared to the control concrete, and are within the range specified by codes, and the 28 days compressive strength of concrete produced by adding 20 – 25 % bacteria and 0.4-0.8% superplasticizer had 28 days compressive strength equal or greater than the control concrete. Also, the 28 days flexural strength of control concrete is significantly higher than flexural strength of all the bio self-compacting concrete, while the split tensile strength of bio self-compacting concrete produced by adding 25% bacteria and 0.4 – 0.8% superplasticizer is higher than the control concrete.

Assessing the Drying Sensitivity of Alkali-Activated Binders Through Mechanical Reliability: Effect of Particle Size and Packing

Despite the steady progress of research on the alkali activation of wastes or subproducts from established industrial processes, the brittleness of the hardened alkali-activated materials frequently results in questionable mechanical reliability, particularly in industrial applications beyond construction materials. This work used a 33 factorial Design of Experiments to examine the effect of three different particle size distributions on the compressive strength and mechanical reliability (Weibull modulus) of a sodium silicate-activated blast-furnace slag under the same processing conditions. As expected, curing temperature and time were strongly correlated, and the corresponding response surfaces showed that, for all studied particle sizes, compressive strengths above 60 MPa with mechanical reliability above 5.0 could be obtained by curing at ~60 °C for ~40 h. The particle size differences caused no significant changes in the extent of alkali activation, as seen in the infrared-spectroscopy results. However, the intersection of the response surfaces showed that a coarser and narrower particle size distribution extended the working area (time × temperature) and favored mechanical reliability. Thus, the precursor’s particle size distribution, which governs particle packing and viscosity during processing, also determines the permeability of the set binder, which affects water removal during drying and the dried binder’s mechanical performance.

OPTIMIZATION OF LC-MS/MS METHOD FOR THE SIMULTANEOUS DETERMINATION OF METFORMIN AND ROSIGLITAZONE IN HUMAN PLASMA WITH BOX-BEHNKEN DESIGN

Objective: The objective of this study was to develop a robust Liquid Chromatography – Tandem Mass Spectrometry (LC-MS/MS) methodology for the precise quantification of metformin and rosiglitazone in human plasma. Methods: A Design of Experiments (DOE) framework was utilized, specifically employing a Box-Behnken experimental design, to optimize critical parameters such as Capillary voltage, Cone voltage, Desolvation temperature, and Collision energy. Sample preparation involved protein precipitation using acetonitrile, simplifying the procedure. Chromatography was performed with a mobile phase of 0.1% formic acid and acetonitrile (60:40 V/V) to enhance sensitivity and reproducibility. Quantification was achieved through Multiple Reaction Monitoring (MRM) of the transition’s m/z 130.1 → m/z 60.1 for metformin, m/z 358.2 → m/z 134.9 for rosiglitazone, and m/z 206.3 → m/z 59.9 for phenformin. The methodology was validated according to regulatory guidelines. Results: The developed methodology demonstrated selectivity, linearity, accuracy, precision, recovery, and stability. The calibration curve showed linearity over the concentration range of 5 ng/ml to 1000 ng/ml for metformin and 1.5 ng/ml to 300 ng/ml for rosiglitazone. Accuracy and precision were within acceptable limits across calibration and quality control standards. Assessments of extraction recovery and matrix effects confirmed the robustness of the extraction procedure, with negligible interference from plasma components. Stability studies indicated that the method maintained acceptable limits for metformin and rosiglitazone concentrations under various storage and handling conditions. Conclusion: The validated Liquid Chromatography – Tandem Mass Spectrometry (LC-MS/MS) methodology provides a reliable and accurate platform for the quantification of metformin and rosiglitazone in human plasma. This method shows potential applications in pharmacokinetic studies and clinical research, ensuring consistent performance in routine analysis.

Electrochemical C−O and C−N Arylation using Alternating Polarity in flow for Compound Libraries

AbstractEtherification and amination of aryl halide scaffolds are commonly used reactions in parallel medicinal chemistry to rapidly scan structure–activity relationships with abundant building blocks. Electrochemical methods for aryl etherification and amination demonstrate broad functional group tolerance and extended nucleophile scope compared to traditional methods. Nevertheless, there is a need for robust and scale‐transferable workflows for electrochemical compound library synthesis. Herein we describe a platform for automated electrochemical synthesis of C−X arylation (X=NH, OH) in flow to access compound libraries. A comprehensive Design of Experiment (DoE) study identifies an optimal protocol which generates high yields across&gt;30 aryl halide scaffolds, diverse amines (including electron‐deficient sulfonamides, sulfoximines, amides, and anilines) and alcohols (including serine residues within peptides). Reaction sequences are automated on commercially available equipment to generate libraries of anilines and aryl ethers. The unprecedented application of potentiostatic alternating polarity in flow is essential to avoid accumulating electrode passivation. Moreover, it enables reactions to be performed in air, without supporting electrolyte and with high reproducibility over consecutive runs. Our method represents a powerful means to rapidly generate nucleophile independent C−X arylation compound libraries using flow electrochemistry.

BOX-BEHNKEN DESIGN ASSISTED ECO-FRIENDLY RP-HPLC-PDA METHOD FOR THE QUANTIFICATION OF PACLITAXEL: APPLICATION TO EVALUATE THE SOLUBILITY OF PACLITAXEL-CYCLODEXTRIN COMPLEX

Objective: Paclitaxel (PTX) is one of the oldest chemotherapeutic agents for cancer treatment. However, PTX is a class IV drug under the Biopharmaceutical Classification System (BCS), and its oral administration is restricted due to its low bioavailability. Complexing PTX with Beta-Cyclodextrin (β-CD) is an option to overcome the low solubility and bioavailability. This study aims to optimize and develop an RP-HPLC analytical method for quantifying PTX from the fabricated β-CD complex. Methods: The HPLC settings were optimized using Design-of-Experiments (DOE) software. The independent variables for the optimization process were buffer ratio, buffer pH, flow rate, and injection volume. The responses were Retention Time (RT), peak area, Tailing Factor (TF), and number of Theoretical Plates (TP) of PTX. The validated method was then used to measure the % entrapment from the PTX-β-CD complex. Results: The developed and optimized RP-HPLC method was validated as per International Council for Harmonisation (ICH) Q2 (R1) guidelines. The developed method showed linearity R2 = 0.999 with a 0.5-20 µg/ml range. The Limit of Detection (LOD) and Limit of Quantification (LOQ) were 95 and 125 ng/ml, respectively. The accuracy and precision for the developed method came under the acceptance criteria. The developed method was used to evaluate the enhancement of solubility of the prepared PTX-β-CD complex. The method was also used in the evaluation of % drug loading, % drug release and stability of the PTX-β-CD complex. The study clearly showed that the solubility of PTX increased from 0 to 1.14±0.53 µg/ml at pH 1.2 and 0 to 3.18±0.61 µg/ml at pH 6.8, respectively. The PTX-β-CD complex showed 73±3.75% drug release in 120 min at pH 1.2 and 87±3.51% at pH 6.8. The developed RP-HPLC method was found to be eco-friendly as per the Analytical Greenness (AGREE) metric approach and software analysis. Conclusion: An eco-friendly RP-HPLC analytical method was successfully developed and optimized for the quantification of PTX from the PTX-β-CD complex.

RESPONSE SURFACE METHODOLOGY (RSM) AS A TOOL IN PHARMACEUTICAL FORMULATION DEVELOPMENT

Response surface methodology (RSM) serves as a valuable tool in pharmaceutical formulation development, facilitating the optimization of drug formulations by systematically exploring the effects of multiple variables on desired responses. This methodology involves the design of experiments to generate mathematical models that predict the relationship between formulation parameters and critical quality attributes. By utilizing statistical techniques such as factorial design, central composite design, and Box-Behnken design, RSM enables the identification of optimal formulation conditions while minimizing the number of experimental trials. Across iterative experimentation and model refinement, RSM assists in understanding the complex interactions between formulation components, process variables, and product characteristics. In this review, we discuss the application of RSM in pharmaceutical formulation studies, highlighting its efficacy in optimizing drug delivery systems, enhancing product stability, and ensuring quality control. In addition, we explore recent advancements in RSM-driven approaches, including its integration with computational modeling and artificial intelligence techniques for enhanced formulation design and process optimization. Overall, RSM offers a systematic and efficient approach for developing robust pharmaceutical formulations, thereby accelerating the drug development process and improving therapeutic outcomes.

Selective leaching of rare earths, base metals and precious metals from used smartphones

ABSTRACT Discarded smartphones represent a valuable source of rare earths (REE), base metals and precious metals. This study focussed on the optimisation of three-stage selective leaching conditions for REE, copper and precious metals (Au and Ag), respectively, contained in printed circuit boards (PCBs) found in end-of-life smartphones. The effects of several leaching conditions, such as sulphuric acid and thiourea concentrations, were investigated using a statistical approach based on a design of experiments using Box–Behnken methodology. Optimum leaching efficiencies were achieved when PCB powder was contacted (solid concentration of 100 g/L) with (1) a 0.2 M H2SO4 solution for 30 min at a temperature of 20°C for REEs; (2) a 1 M H2SO4 solution with 67 g H2O2/L for 180 min at 80°C for Cu and (3) a solution of 42 g thiourea/L in 0.1 M H2SO4 and 9 g Fe2(SO4)3/L for 120 min at 20°C for Au and Ag. Using these optimal conditions, a complete leaching procedure included an REE solubilisation step and a base metal leaching step, both repeated twice, and a precious metal leaching step. This procedure solubilised 91% of the REE, 100% of the copper, 98% of the gold and 87% of the silver contained in the PCB powder during their respective leaching stages.