D-optimal Experimental Design Research Articles

The Algorithm of Gu and Eisenstat and D-Optimal Design of Experiments

This paper addresses the following problem: given m potential observations to determine n parameters, m>n, what is the best choice of n observations. The problem can be formulated as finding the n×n submatrix of the complete m×n observation matrix that has maximum determinant. An algorithm by Gu and Eisenstat for a determining a strongly rank-revealing QR factorisation of a matrix can be adapted to address this latter formulation. The algorithm starts with an initial selection of n rows of the observation matrix and then performs a sequence of row interchanges, with the determinant of the current submatrix strictly increasing at each step until no further improvement can be made. The algorithm implements rank-one updating strategies, which leads to a compact and efficient algorithm. The algorithm does not necessarily determine the global optimum but provides a practical approach to designing an effective measurement strategy. In this paper, we describe how the Gu–Eisenstat algorithm can be adapted to address the problem of optimal experimental design and used with the QR algorithm with column pivoting to provide effective designs. We also describe implementations of sequential algorithms to add further measurements that optimise the information gain at each step. We illustrate performance on several metrology examples.

Post-combustion CO2 capturing by KOH solution: An experimental and statistical optimization modeling study

A pilot-scale bubble column contactor has been utilized for carbon dioxide chemisorption from simulated flue gas in the temperature range 30°C to 50°C. The influence of the most important operating parameters has been investigated. A total of 25 experiments were designed using the response surface methodology (RSM) and were then carried out in the bubble contact column. The results revealed that the liquid volume in the column, the alkaline concentration, and the temperature had a positive effect, while the gas hold-up had a negative effect on the CO2 removal efficiency. A statistical model has been developed using the RSM D-optimal experimental design method. To achieve the highest CO2 chemisorption, several operating conditions have been optimized. The model predicted that the maximum percentage of carbon dioxide removal would be 86.64%, and under the same operating conditions the experimental removal efficiency was 87.12%.

Polar licit and illicit ingredients in dietary supplements: chemometric optimization of extraction and HILIC-MS/MS analysis

Many dietary supplements claim the ability to enhance sports performance and to improve the fitness of the consumers. Occasionally, along with legal ingredients, illicit compounds may be added without being labelled, leading to unintended doping. Hence, the aim of this study was to develop an analytical method to determine a set of 12 polar (logDpH=7 from −2.0 to +0.3) compounds including diuretics, stimulants, β2-agonists, methylxanthines, and sweeteners. Hydrophilic interaction liquid chromatography was chosen as separation strategy, coupled with tandem mass spectrometry. The instrumental method was optimized using a two-step design of experiments (DoE). Firstly, a Plackett–Burman (PB) DoE was performed to identify the more influencing variables affecting peak areas and chromatographic resolution among temperature, water percentage in the mobile phase, and flow rate, as well as type and concentration of buffers. Secondly, a D-optimal DoE was set, considering only the most significant variables from the PB-DoE results, achieving a deeper understanding of the retention mechanism. Sample processing by salt-assisted liquid–liquid extraction was studied through DoE as well, and the whole method showed recoveries in the range 40–107% and procedural precision ≤11% for all analytes. Finally, it was applied to real samples, in which the four methylxanthines and two artificial sweeteners were detected and quantified in the range of 0.02–192 mg g−1. These values were compared to the quantities declared on the DS labels, when possible. Furthermore, a sequence of MS/MS scans allowed detection of a signal in one of the samples, structurally similar to the β2-agonist clenbuterol.Graphical

Improvement of ferrioxalate assisted Fenton and photo-Fenton processes for paracetamol degradation by hydrogen peroxide dosage.

This work aimed to investigate the impact of hydrogen peroxide (HP) punctual dosage on paracetamol (PCT) degradation, through Fenton and photo-Fenton processes under near-neutral pH conditions, using ferrioxalate and artificial sunlight. The assays were performed using a D-optimal experimental design, to statistically evaluate the influence of radiation (ON or OFF), HP concentration (94.5-756mg L-1), and HP dosage (YES or NO), on PCT conversion. The optimal conditions determined from the study were: HP = 378mg L-1, DOS = YES, and RAD = ON, achieving a predicted PCT conversion of 99.68% in 180min. This result obtained from the model was very close to the experimental one (98.80%). It was verified that HP dosage positively influenced the iron catalytic cycle since higher Fe2+ concentrations were reached at shorter reaction times, accelerating not only PCT conversion but also its by-products hydroquinone and 1,4-benzoquinone, leading to better performances of Fenton and photo-Fenton reactions. Under optimal conditions and employing real water matrices (an artificial matrix with inorganic anions, a real groundwater sample, and a synthetic industrial wastewater), HP dosage demonstrated the ability to mitigate the negative effects caused by the content of different ions and other organic compounds and significantly improve HP consumption in challenging wastewater conditions.

Cell uptake and intracellular trafficking of bioreducible poly(amidoamine) nanoparticles for efficient mRNA translation in chondrocytes.

Disulfide-containing poly(amidoamine) (PAA) is a cationic and bioreducible polymer, with potential use as a nanocarrier for mRNA delivery in the treatment of several diseases including osteoarthritis (OA). Successful transfection of joint cells with PAA-based nanoparticles (NPs) was shown previously, but cell uptake, endosomal escape and nanoparticle biodegradation were not studied in detail. In this study, C28/I2 human chondrocytes were transfected with NPs co-formulated with a PEG-polymer coating and loaded with EGFP mRNA for confocal imaging of intracellular trafficking and evaluation of transfection efficiency. Compared with uncoated NPs, PEG-coated NPs showed smaller particle size, neutral surface charge, higher colloidal stability and superior transfection efficiency. Furthermore, endosomal entrapment of these PEG-coated NPs decreased over time and mRNA release could be visualized both in vitro and in live cells. Importantly, cell treatment with modulators of the intracellular reducing environment showed that glutathione (GSH) concentrations affect translation of the mRNA payload. Finally, we applied a D-optimal experimental design to test different polymer-to-RNA loading ratios and dosages, thus obtaining an optimal formulation with up to ≈80% of GFP-positive cells and without toxic effects. Together, the biocompatibility and high transfection efficiency of this system may be a promising tool for intra-articular delivery of therapeutical mRNA in OA treatment.

Modification of PA66 fibres with in-situ polymerisation of 2- hydroxyethylmethacrylate

Poly(hydroxyethylmethacrylate) (pHEMA) was successfully introduced as an adhesion promotion layer on polyamide 66 (PA66) fibre surface by graft polymerisation using hydrogenperoxide as initiator. The grafted pHEMA layer strongly changes the fibre surface chemistry by introducing oxygen containing groups that thereby improve the fabric's wettability and strengthen the interface to potential subsequent coating layers or matrix material in case of fibre reinforced composites. The grafting reaction and formation of grafted pHEMA could be monitored and verified using different microscopic and spectroscopic analytical techniques, e.g. SEM, FTIR and NMR. Furthermore, the influence of parameters such as time, temperature and post plasma treatment of the grafting process on the yield of pHEMA was investigated and optimised using a d-optimal experimental design. For the optimisation of the process, the design suggested short treatment times at lower process temperatures and plasma post treatment for the desired fabric properties as an improved wettability and minimised change on bulk properties.

Process model design for positive displacement compressors and their experimental validation: Comparison of Optimal Experimental Design and Machine Learning

Valid simulation models play a critical role in enhancing efficiency in development processes and minimizing experimental efforts. As a result, ensuring accurate predictions through model discrimination, Model Calibration, and Validation (MoCaVal) has become increasingly important and is a necessary step to analyze the behavior and evaluate the effectiveness of systems during their initial design stages. Additionally, to achieve the climate objectives, it is imperative that heat pumps predominantly perform the building sector’s heating. The effectiveness of heat pumps hinges on the performance of the compressor. Therefore, there is a requirement for valid compressor models. However, currently, there is no universal compressor model that applies to all refrigerants and designs. Therefore, every refrigerant or design modification requires the development or adaptation of models. Since creating new models is a time-consuming procedure, automated techniques are advantageous.This paper compares two automated model development methods, Optimal Experimental Design (OED) and Machine Learning (ML), to create valid simulation models within the MoCaVal framework. OED is used to calibrate existing simulation models, while ML is employed to develop new models. Our comparison of the two methods focuses on a fixed-speed scroll compressor of 4 kW nominal power, using R410A and featuring 51 measurement points. Using the Full Factorial Plan (FFP) and the D-Optimal Experimental Design (D-OED), predefined models for mass flow rate, electrical power, isentropic and volumetric efficiency were calibrated. Employing the FFP, Machine Learning (ML) was also applied through support vector regression.The OED reduces experimental effort by 75–90 % compared to the FFP while only slightly increasing the average uncertainty by 0.30–0.79 %. For the FFP, MoCaVal achieved uncertainties of 0.52–3.9 % for calibrated models and 0.34–0.56 % with ML models. Therefore, within the design space, ML outperforms calibrated models based on the FFP and OED regarding uncertainty. However, since machine learning models were trained on the FFP, additional research is needed to demonstrate their potential for reducing test time and extrapolating results.

Determination of polycyclic aromatic hydrocarbons in bud-derived supplements by magnetic molecular imprinted microparticles and GC-MS: D-optimal design for a fast method optimization

Within the world of natural food supplements, organic extracts deriving from young plant meristematic tissue (bud-derivatives) are becoming attractive, thanks to their richness in bioactive molecules. This natural source is scarce, but every year, tons of plant material, including buds, come from city pruning. If this sustainable source is rather promising from a circular economy point of view, the safety of the obtained supplements must be assessed. In fact, anthropic microcontaminants, such as polycyclic aromatic hydrocarbons (PAHs), could adsorb onto the urban buds, leading to a possible contamination of the bud-derivatives. In this study, we developed a magnetic dispersive solid phase extraction (m-dSPE) based on molecularly imprinted microparticles, combined with GC-MS, to quantify the 16 priority PAHs in such extracts. The D-optimal experimental design was implemented to maximize analytes’ recovery with the smallest set of experiments. The optimized method was characterized by great selectivity thanks to the molecular imprinted polymer and ease of use provided by m-dSPE. Moreover, it complies with green principles, thanks to the minimum consumption of organic solvent (1.5 mL of acetone per sample). The recoveries ranged from 76 to 100% and procedural precision was below 10% for most PAHs. Despite the matrix complexity, low quantification limits (0.7–12.6 μg kg−1) were reached. This guaranteed the PAHs’ quantitation at levels below those indicated as safe by a European Community regulation on food supplements. None of the analyzed samples, coming from different anthropically impacted areas, showed concerning PAHs levels.

Grain size and temperature evolutions during linear friction welding of Ni-base superalloy Waspaloy: Simulations and experimental validations

This research study was aimed at investigating the influence of linear friction welding parameters on grain size alteration and temperature distribution of Ni-base superalloy Waspaloy. A 3D finite element model was developed to predict average grain size and peak temperature as responses. The linear friction welding parameters consisted of oscillation amplitude, oscillation frequency, and applied pressure. Initially, the evolution of the average grain size as a function of the most influential process parameters was subsequently modeled based on the Johnson-Mehl-Avrami-Kolmogorov recrystallization model and were then validated with experimental results. Then, D-optimal design of experiments and analysis of variance were conducted to determine the most influential process parameters that affect the average grain size and peak temperature of the welded joint. Thereafter, response surface method was employed to obtain the regression models of the responses. The analysis of variance demonstrated that the P-value of the regression models was smaller than 5% and R2, Radj2, and RPred2 were between 87% and 97%, which showed that the predictive regression models of PT and AGS can be used with a high level of confidence. The regression models were then validated by selecting two extra LFW tests in the space of the DoE. The optimum values of the welding parameters were determined to minimize the responses. The multi-criteria optimization analysis showed that both average grain size and peak temperature were more dependent on pressure than oscillation amplitude and frequency. The developed finite element and regression models can be utilized as a predictive tool for the design of joining industrial components, which minimize expensive and time-consuming experimental tests and measurements.

Optimization of a Mucoadhesive Vaginal Gel Containing Clotrimazole Using a D-Optimal Experimental Design and Multivariate Analysis.

The aim of this study was to develop a suitable clotrimazole (CLT)-loaded mucoadhesive vaginal gel (CLT-MVG) for topical applications in vaginal candidiasis. Ten CLT-MVG formulations were prepared, consisting of mixtures of acid polyacrylic (Carbopol 940) and polyethene oxides, Sentry Polyox WSRN 1105 or 750, according to an experimental D-optimal design, and CLT was suspended at a ratio of 1%. The prepared CLT-MVG formulations were studied in vitro, and the formulation containing Carbopol 940 0.89% combined with PEO 1105 1.39% was identified with the optimal rheological and in vitro bioadhesion properties, ensuring the prolonged release of CLT, with a similarity factor greater than 50, indicating dissolution profile similarity for three batches of the optimized formulation. This optimized formulation showed a pH in the tolerance range, and an adequate ex vivo mucoadhesion time, while the FT-IR studies revealed no interactions between the excipients and CLT. The microscopic analysis identified a mean particle size of suspended CLT of 5.24 ± 0.57 μm. The in vitro antifungal activity of the optimized formulation was tested on twenty strains of Candida albicans and proved to be better compared to a marketed clotrimazole preparation, showing a greater inhibition effect (p < 0.05). The optimized formulation could be a good candidate for the local treatment of vaginal mycosis.

Investigations into the stability of anthocyanins in model solutions and blackcurrant juices produced with various dejuicing technologies

Blackcurrant juices were produced with an oxygen-excluding spiral filter press and two conventional pressing systems exerting common oxygen exposure at pilot plant scale (200 kg) in technological duplicate in two subsequent years (n = 4). In contrast to findings on previously studied fruits, contents of total and individual anthocyanins were not significantly higher after spiral filter (1636–1872 mg/L) than after conventional pressing (1529–2083 mg/L). During storage for 52 weeks at 4, 20 and 37 °C, anthocyanin levels depended strongly on storage temperature, but not on the used pressing system (conventional vs. oxygen-reduced). Other juice quality parameters like ascorbic acid behaved likewise. Furthermore, a D-optimal design of experiments was used to study the influence and interactions of the factors oxygen, ascorbic acid, sugar and pH value on anthocyanin levels during a heat treatment in a model solution made with preparatively isolated blackcurrant anthocyanins. In agreement with our production trials at pilot plant scale, oxygen levels were only marginally important for the rate of anthocyanin degradation, but the influence of sugar content, ascorbic acid content and pH value was highly relevant as discussed in this report.

Coagulation/flocculation process using Moringa oleifera bio-coagulant for industrial paint wastewater treatment: optimization by D-optimal experimental design

Coagulation/flocculation process using Moringa oleifera bio-coagulant for industrial paint wastewater treatment: optimization by D-optimal experimental design

Efficient Development of Green Emulsifier/Emollient-Based Emulsion Vehicles: From RSM Optimal Experimental Design to Abridged In Vivo Assessment.

Since natural-origin, sustainable ingredients are preferred by modern consumers, novel emulsifiers and emollients keep entering the market. This study hypothesizes that a combination of in silico, instrumental tools and simplified sensory studies could be used to efficiently characterize emulsions in a shorter timeframe. A total of 22 rather simple o/w emulsions were prepared by a time/energy-saving emulsification process. A natural mixed emulsifier (Lauryl Glucoside/Myristyl Glucoside/Polyglyceryl-6 Laurate) and two emollients (both with INCI name C15-19 Alkane) were used. The performed D-optimal experimental design within the response surface method (RSM) significantly narrowed down the number of samples about to enter the stage of texture, friction and sensory studies to the samples comprising 30% of a respective Emogreen emollient and 2% or 3% of the emulsifier. The sample comprising 2% emulsifier/30% Emogreen® L15 showed significantly higher firmness (42.12 mN) when compared to the one with 2% emulsifier/30% Emogreen® L19 (33.62 mN), which was somewhat unexpected considering the emollients' inherent viscosity values (4.5 mPa·s for L15 and 9 mPa·s for L19). The sample with 2% emulsifier/30% Emogreen® L19 managed to maintain the lowest friction, while the one with 3% emulsifier/30% Emogreen® L19 released its full lubricating potential in the second part of the measurement (30-60 s). The obtained results revealed the strengths and weaknesses of each formulation, narrowing down their possible applications in the early development stage.

Multi-Objective Modified Differential Evolution Methods for the Optimal Parameters of Aluminum Friction Stir Welding Processes of AA6061-T6 and AA5083-H112

This study introduces a modified differential evolution approach (MoDE) for evaluating the optimal objective and parameter values of the friction stir welding (FSW) process of dissimilar materials: AA5083 and AA6061. The aim of this study is to investigate the ultimate (UTS), maximum hardness (MH), and minimum heat input (HI) of the weld zone. The controlled welding parameters were shoulder diameter, rotation speed, welding speed, tilt angle, pin type, reinforcement particle type, and tool pin movement direction. The D-optimal experimental design method was used to create the experiment and obtain the mathematical model for optimizing the targeted objectives. The optimal rotational speed, welding speed, shoulder diameter, tilt angle, pin-type, additive type, and tool pin movement are 1162.81 rpm, 52.73 mm/min, 21.17 mm, 2.37 degrees, straight cylindrical, silicon carbide, and straight movement direction, respectively. The optimal values for UTS, MH, and HI are 264.68 MPa, 105.56 HV, and 415.26 °C, respectively. The MoDE outcome exceeded particle swarm optimization (PSO), the original differential evolution algorithm (DE), and the D-optimal design (experiment) results. The MoDE provides better UTS, MH, and HI than other approaches by an average of 8.04%, 4.44%, and 2.44%, respectively. In particular, when comparing results produced by using various approaches, we discovered that the MoDE results are 7.45%, 4.45%, and 3.50% better than PSO, DE, and the experimental results, respectively. All methods were evaluated for their reliability by comparing the results of actual experiments to those predicted by theory, and we discovered that the MoDE yielded the smallest percentage difference between the two, at 1.49%, while PSO and DE yielded differences of 5.19% and 3.71%, respectively.

Bayesian D-Optimal Design of Experiments with Quantitative and Qualitative Responses

Systems with both quantitative and qualitative responses are widely encountered in many applications. Design of experiment methods are needed when experiments are conducted to study such systems. Classic experimental design methods are unsuitable here because they often focus on one type of response. In this paper, we develop a Bayesian D-optimal design method for experiments with one continuous and one binary response. Both noninformative and conjugate informative prior distributions on the unknown parameters are considered. The proposed design criterion has meaningful interpretations regarding the D-optimality for the models for both types of responses. An efficient point-exchange search algorithm is developed to construct the local D-optimal designs for given parameter values. Global D-optimal designs are obtained by accumulating the frequencies of the design points in local D-optimal designs, where the parameters are sampled from the prior distributions. The performances of the proposed methods are evaluated through two examples.

Preparation and optimization of a lignin-based pressure-sensitive adhesive

D-optimal designs were applied to find the best parameters for the preparation of lignin-based pressure-sensitive adhesives (PSA) for sticky notes. Organosolv lignin was directly incorporated into a polycarboxylate polyether (PCE)/water matrix. The independent variables considered in the experimental design were the ratio between PCE, lignin, and water and the curing parameters. The distance traveled by the ball (tack), the peel-off losses and the final water content were the analyzed responses that allowed the optimization of the PSA formulation. The accuracy, the precision and the efficiency of the model were evaluated during the first experimental design for the formulation of the lignin-based adhesive named DES-OL-ADH. This formulation was optimized during the second experimental design abbreviated DES-OL-OPT. The coefficients of determination of the tack, the peel-off losses and the final water content were 0.98, 0.99 and 0.99, respectively. The model was satisfactory which allows the optimization of the PSA formulation. The DES-OL-OPT suggests that lignin-based PSA can be prepared as a sticky note application with 5 wt% of lignin, 84 wt% of PCE and 11 wt% of added water in the oven at 130 °C for 60 min, which shows a higher tackiness and similar peel-off losses than the commercial sticky notes PSAs.•Protocol optimization for the preparation of a green pressure sensitive adhesive (PSA) from PCE polymer, lignin, and water.•Influence of 5 compositional or processing parameters on adhesive performance through a 2-steps d-optimal experimental design.•Development of a new method, based on peel-off losses, to assess the performance of a PSA.

Difference between the Effects of Peripheral Sensory Nerve Electrical Stimulation on the Excitability of the Primary Motor Cortex: Examination of the Combinations of Stimulus Frequency and Duration.

Peripheral sensory nerve electrical stimulation (PES) excites the primary motor cortex and is expected to improve motor dysfunction post-stroke. However, previous studies have reported a variety of stimulus frequencies and stimulus duration settings, and the effects of these different combinations on primary motor cortex excitability are not clear. We aimed to clarify the effects of different combinations of stimulus frequency and stimulus duration of PES on the excitation of primary motor cortex. Twenty-one healthy individuals (aged &gt; 18 years, right-handed, and without a history of neurological or orthopedic disorders) were included. Each participant experienced three different stimulation frequencies (1, 10 and 50 Hz) and durations (20, 40 and 60 min). Motor-evoked potentials (MEPs) were recorded pre- and post-PES. The outcome measure was the change in primary motor cortex excitability using the MEP ratio. We used a D-optimal design of experiments and response surface analysis to define the optimal combination within nine different settings inducing more satisfying responses. The combination of stimulation frequency and stimulation time that maximized the desirability value was 10 Hz and 40 min, respectively. The results of this study may provide fundamental data for more minimally invasive and effective implementation of PES in patients with stroke.

An efficient process for improvement of biohydrogen and biomethane production from tomato waste: Inhibitory effects of ultrasonic pretreatment

The present study was undertaken to determine the effect of ultrasonic pretreatment of tomato wastes on improving the production of bio-H2 and bio-CH4. Furthermore, inhibitory effects of phenolic and tannin compounds that may be produced during the breaking of complex structures using the ultrasonic irradiations were investigated. For this purpose, anaerobic digestion of different mixtures of tomato waste and cow manure, ultrasonically pretreated with different acoustic powers and sonication times, was studied based on a combined d-optimal experimental design. A two-stage optimization process was developed by integrating multivariate modeling and desirability analysis. The first stage of the optimization process showed that the ultrasonic pretreatment of 197.21 W (0.33 W/mL) at 21.47 min for the mixtures with high amounts of tomato wastes (>90 %) produced small amounts of the total phenolic compounds (2.03 mg equivalent gallic acid/g: mg/g) and tannin content (4.37 mg catechin equivalent/g: mg/g). These conditions produced high amounts of total solid (6.53 %), total volatile solid (77.84 %) and total carbohydrate (6.95 mg glucose equivalent/g: mg/g). These values led to producing Bio-H2 > 18 %vol and Bio-CH4 > 2 %vol. The second stage of the optimization process indicated that total phenolic compounds < 12.5 mg/g and tannin content < 25.5 mg/g were needed to maximize both bio-H2 and bio-CH4 production and optimize the desirability of biogas production.

Optimisation of working parameters for lactic acid bacteria and yeast recovery from table olive biofilms, preserving fruit integrity and reducing chloroplast recovery

The study of the table olive biofilms is usually achieved using a stomacher which causes the physical rupture of pitted olives in an osmotic media but does not differentiate between those on the surface and inside the fruits. Besides, the high amount of eukaryotic DNA released from the vegetable cells makes the further molecular study of the detached microbiota complex. This work applies Response Surface Methodology, based on a D-optimal experimental design and glass beads, to recover lactic acid bacteria (LAB) and yeasts from the biofilm of fermented olives without crushing the flesh. The RSM showed that the best simultaneous results were obtained by shelling the olives, at 8 °C, with glass beads (6 mm diameter) in a 0.16 (w/w) bead/olive ratio for 15 min at 330–400 rpm. Its application recovered lower LAB (possibly because of excluding those in the flesh), but similar yeast counts to the stomacher. The metataxonomic analysis of total DNA from biofilms showed that the glass bead-based protocol reduced the chloroplast sequences and improved the genera assignation for bacteria (16S) and yeast (ITS). The new non-destructive procedure enhances biofilm studies and may allow validating table olives as a carrier of probiotic microorganisms.

Liquid-phase microextraction using the microfluidic chip for the extraction of mesalazine from water and biological samples

For the first time, a microfluidic device-based liquid phase microextraction followed by HPLC-UV analysis was introduced and optimized by response surface methodology (RSM) for the extraction and determination of mesalazine. Two symmetrical micro-channels separated by a support liquid membrane formed the microfluidic chip for passive diffusion of the target from the donor phase to the acceptor phase. The effects of the main variables, including the flow rate, pH of donor and acceptor phases, and solvent type, as well as their interactions were investigated on the extraction efficiency of the mesalazine and optimized by the D-optimal experimental design. The predicted extraction efficiency percentage of mesalazine at the optimal conditions (flow rate, 0.0197 mL/min; donor phase pH, 5.4; acceptor phase pH, 11.9; and solvent, 1-Butanol) was 100% and confirmed by its experimental value with an error of 0.1%. In addition, the procedure provided an acceptable repeatability with relative standard deviations lower than 2%, a detection limit of 0.81 ng/mL, and a quantitation limit of 2.7 ng/mL. This microfluidic chip was successfully applied for the determination of mesalazine in human plasma and urine samples with extraction efficiencies within the range of 88–92%. The proposed method provides advantages such as reduced sample consumption and extraction time, low cost, portability, and high extraction efficiency compared to the existing sample preparation techniques for mesalazine.