Experimental design in chromatography: A tutorial review

From lab to industrial development of lipid nanocarriers using quality by design approach

Lipid nanocarriers have attracted a great deal of interest in the delivery of therapeutic molecules. Despite their many advantages, compliance with quality standards and reproducibility requirements still constrain their industrial production. The relatively high failure rate in lipid nanocarrier research and development can be attributed to immature bottom-up manufacturing practices, leading to suboptimal control of quality attributes. Recently, the pharmaceutical industry has moved toward quality-driven manufacturing, emphasizing the integration of product and process development through the principles of quality by design. Quality by design in the pharmaceutical industry involves a thorough understanding of the quality profile of the target product and involves an assessment of potential risks during the design and development phases of pharmaceutical dosage forms. By identifying essential quality characteristics, such as the active ingredients, excipients and manufacturing processes used during research and development, it becomes possible to effectively control these aspects throughout the life cycle of the drug. Successful commercialization of lipid nanocarriers can be achieved if large-scale challenges are addressed using the QbD approach. QbD has become an essential tool because of its advantages in improving processes and product quality. The application of the QbD approach to the development of lipid nanocarriers can provide comprehensive and remarkable knowledge enabling the manufacture of high-quality products with a high degree of regulatory flexibility. This article reviews the basic considerations of QbD and its application in the laboratory and large-scale development of lipid nanocarriers. Furthermore, it provides forward-looking guidance for the industrial production of lipid nanocarriers using the QbD approach.

Hydrophobic interaction chromatography in continuous flow-through mode for product-related variant removal

Product-related impurities are challenging to remove during monoclonal antibody (mAb) purification process due to molecular similarity. Frontal chromatography on hydrophobic interaction resins has demonstrated its capability to effectively remove such impurities. However, process improvements geared towards purity level comes as a trade-off with the yield loss. In this work, we present a hydrophobic interaction chromatography process using multicolumn continuous chromatography (MCC) concept and frontal analysis to remove a high prevalence product related impurity. This design uses a two-column continuous system where the two columns are directly connected during product chase step to capture product wash loss without any in-process adjustment. This polish MCC operation resulted in a 10 % increase in yield while maintaining 99 % purity, despite the presence of 20 % product-related impurities in the feed material. One challenge associated with polish MCC design is that the accumulation of the impurities renders a non-steady state recycling. To surmount this issue and ensure a robust process, a mechanistic model was developed and validated to predict multicomponent breakthrough. This model was capable to predict multiple cycle behavior and accounts for increased impurity concentration. Assisted by the model, the optimized operation parameters and conditions can be determined to account for variation in product load quality. The simulated results demonstrate an effective doubling of productivity compared to conventional batch chromatography.

Transferability of global retention models in reversed-phase liquid chromatography for natural products

Considerable progress has been made in enhancing resolution in reversed-phase liquid chromatography for the analysis of complex samples, particularly within the field of natural products, through the application of global retention models using multi-linear gradients. Global models effectively differentiate solute retention effects from those originating from the column and solvent, offering predictive capabilities comparable to conventional individual retention models, without the requirement for standards for all compounds. While conventional individual models result in higher accuracy, they frequently demand standards that are unavailable for natural product samples. Moreover, the creation of individual models can be time-consuming due to the need for repetitive work for additional compounds. Experimental validation of global models has demonstrated that the accuracy is enough for the prediction of complex chromatograms. Through a carefully designed experimental work, this study reports the correct determination of global parameters for column and solvent, with excellent consistency across various medicinal plant samples. The successful transfer of predictions and optimisation of resolution across diverse plant species (lemon balm, peppermint, and pennyroyal) is confirmed. This highlights the applicability of predictions using global models across botanical varieties.

Robustness evaluation of weak anion exchange chromatography method for the purity analysis of therapeutic oligonucleotides

Therapeutic oligonucleotides are becoming an important class of therapeutics. Their manufacturing processes can result in the formation of impurities, particularly truncated species. To ensure the quality and safety of the product, it is crucial to evaluate the presence of these species. Liquid chromatography analysis enables such purity determination. In this context, a recently described weak anion exchange chromatography method was optimized to allow the effective separation of different impurities. The optimization addressed the complexity and instability of the mobile phases, which contained salts and organic compounds. Adjustments were made to the mobile phase composition and gradient to meet the requirements of QC laboratories. Additionally, to ensure the method's reliability, a robustness study was conducted based on a risk assessment. Five factors were considered potential risks and were assessed experimentally on different chromatographic outputs. This led to the definition of a robust space, ensuring the method's reliability for the purity determination of oligonucleotides.

A Novel Method for Development and Validation of the Degradation Products Analysis of N-Carbamylglutamate with UHPLC by Using Design of Experiment Approach

Carglumic acid, also known as N-carbamyl-l-glutamic acid, is a medication used in the treatment of a rare genetic disorder called N-acetylglutamate synthase (NAGS) deficiency. To the authors' knowledge, there was no method reported in the literature for the determination of degradation products suitable for quality control analyses of carglumic acid. Thus, the aim of the presented study is to develop an impurity method with a UHPLC/DAD detector configuration compatible with industrial standards from the European Pharmacopeia and the United States Pharmacopeia, making the drug more accessible for developing and underdeveloped countries through its precise evaluation. The method involved the separation of carglumic acid and its degradation products using a reverse-phase C18 column (Waters, BEH 150 mm × 2.1 mm, 1.7 μm) at a flow rate of 0.39 mL/min with a stop time of 10 min. To separate all unknown and known impurities, a gradient elution (phosphate buffer, pH 2.4, and acetonitrile) system was used. The detection was performed at 214 nm. Forced degradation studies were conducted under different stress conditions, including acidic, basic, oxidative, thermal, and photolytic stress. Placket-Burman statistical experimental design was used to demonstrate the robustness of this method, and the suitability of the method was confirmed under the applied conditions. Box-Behnken design was used to provide the optimum resolution between the peaks determined to be critical during the optimization. The developed method was validated according to ICH guidelines for specificity, linearity, accuracy, precision, and robustness. The limit of detection and limit of quantification were 0.7 and 0.15 μg/mL for carglumic acid, respectively.

Development of Thin Film Microextraction with Natural Deep Eutectic Solvents as 'Eutectosorbents' for Preconcentration of Popular Sweeteners and Preservatives from Functional Beverages and Flavoured Waters

An eco-friendly method for the determination of sweeteners (aspartame, acesulfame-K) and preservatives (benzoic acid, sorbic acid, methylparaben, ethylparaben) in functional beverages and flavoured waters using thin film microextraction (TFME) and high-performance liquid chromatography with UV detection (HPLC-UV) was proposed. A series of fourteen green and renewable solidified natural deep eutectic solvents (NADESs) were prepared and tested as 'eutectosorbents' in TFME for the first time. In the proposed method, the NADES containing acetylcholine chloride and 1-docosanol at a 1:3 molar ratio was finally chosen to coat a support. Four factors, i.e., the mass of the NADES, pH of the samples, extraction time, and desorption time, were tested in the central composite design to select the optimal TFME conditions. Limits of detection were equal to 0.022 µg mL-1 for aspartame, 0.020 µg mL-1 for acesulfame-K, 0.018 µg mL-1 for benzoic acid, 0.026 µg mL-1 for sorbic acid, 0.013 µg mL-1 for methylparaben, and 0.011 µg mL-1 for ethylparaben. Satisfactory extraction recoveries between 82% and 96% were achieved with RSDs lower than 6.1% (intra-day) and 7.4% (inter-day). The proposed 'eutectosorbent' presented good stability that enabled effective extractions for 16 cycles with recovery of at least 77%. The proposed NADES-TFME/HPLC-UV method is highly sensitive and selective. However, the use of a solid NADES as a sorbent, synthesized without by-products, without the need for purification, and with good stability on a support with the possibility of reusability increases the ecological benefit of this method. The greenness aspect of the method was evaluated using the Complex modified Green Analytical Procedure Index protocol and is equal to 84/100.

Analytical QbD for the optimization of a multimode HPLC method for the investigation of hydrochlorothiazide, diltiazem and propranolol release from 3D printed formulation

Since 3D printing technology is an emerging field in pharmaceutical technology, the present study aimed at the development of a mixed-mode liquid chromatographic method for the separation and determination of hydrochlorothiazide, diltiazem, and propranolol to investigate their in-vitro release performance from 3D printed tablets. Due to the unique properties of the mixed-mode stationary phase, the three drugs were separated in less than 8 min under isocratic elution. Method development was accomplished following the Analytical Quality by Design principles and was evaluated using risk assessment and multivariate analysis. The influences of critical method parameters on critical method attributes (were screened using a 2-level fractional factorial design and subsequently optimized through a central composite design. The method operable design region was approved by the establishment of a robust zone using Monte Carlo simulation and capability analysis. The validation of the HPLC method was performed based on the total error concept. The relative bias was varied between ─ 11.6 % and 10.5 % and the RSD values for repeatability and intermediate precision were below 4.4 % in all cases. The limits of detection (LOD) ranged between 0.17 - 0.90 μg/mL and were adequate for the specific application. The developed method was successfully applied to the analysis of the studied drugs in in-vitro drug release samples obtained from 3D-printed tablets combining the above-mentioned active pharmaceutical ingredients (APIs).

Is it advantageous to use quality by design (QbD) to develop nanoparticle-based dosage forms for parenteral drug administration?

Parenteral administration is one of the most commonly used drug delivery routes for nanoparticle-based dosage forms, such as lipid-based and polymeric nanoparticles. For the treatment of various diseases, parenteral administration include intravenous, subcutaneous, and intramuscular route. In drug development phase, multiparameter strategy with a focus on drug physicochemical properties and the specificity of the administration route is required. Nanoparticle properties in terms of size and targeted delivery, among others, are able to surpass many drawbacks of conventional dosage forms, but these unique properties can be a bottleneck for approval by regulatory authorities. Quality by Design (QbD) approach has been widely utilized in development of parenteral nanoparticle-based dosage forms. It fosters knowledge of product and process quality by involving sound scientific data and risk assessment strategies. A full and comprehensive investigation into the state of implementation and applications of the QbD approach in these complex drug products can highlight the gaps and challenges. In this review, the analysis of critical attributes and Design of Experiment (DoE) approach in different nanoparticulate systems, together with the proper utilization of Process Analytical Technology (PAT) applications are described. The essential of QbD approach for the design and development of nanoparticle-based dosage forms for delivery via parenteral routes is discussed thoroughly.

Utilizing experimental design and desirability function in optimizing RP-HPLC method for simultaneous determination of some skeletal muscle relaxants and analgesics

An experimental design and response surface methodologies using Plackett-Burman and Box-Behnken designs were applied for selecting and optimizing the most appropriate parameters which significantly affect the separation and quantitative estimation of five skeletal muscle relaxants and four analgesic drugs (baclofen, methocarbamol, dantrolene sodium, orphenadrine citrate, cyclobenzaprine hydrochloride, ketoprofen, etoricoxib, ibuprofen, and mefenamic acid) with a relatively short duration of analysis in a single run. For the separation of the nine drugs, an INERTSIL ODS-V3-5 µm C18 column (250 × 4.6 mm I.D.) was used with the optimum mobile phase conditions (45.15 mM ammonium acetate buffer pH 5.56 adjusted with acetic acid, acetonitrile, and methanol in a ratio of 30.5:29.5:40, v/v/v with a flow rate of 1.5 mL/min) and UV-detection at 220 nm. The optimized method was successfully subjected to the validation steps as described in ICH guidelines for linearity, precision, accuracy, robustness, and sensitivity. The optimized and validated method was effectively applied to determine the content of the studied drugs in their pharmaceutical preparations and to expand its applicability to the counterfeit estimation of etoricoxib in different brands of tablet dosage forms.

Phase separation methods for protein purification: A meta-analysis of purification performance and cost-effectiveness

Protein purifications based on phase separations (e.g., precipitation and liquid-liquid extraction) have seen little adoption in commercial protein drug production. To identify barriers, we analyzed the purification performance and economics of 290 phase separation purifications from 168 publications. First, we found that studies using Design of Experiments for optimization achieved significantly greater mean yield and host cell protein log10 removal values than those optimizing one factor at a time (11.5% and 53% increases, respectively). Second, by modeling each reported purification at scales from 10 to 10,000 kg product/year and comparing its cost-effectiveness versus chromatography, we found that cost-effectiveness depends strongly on scale: the fraction of phase separations predicted to be cost-effective at the 10, 100, and 1000 kg/year scales was 8%, 15%, and 43%, respectively. Total cost per unit product depends inversely on input purity, with phase separation being cheaper than chromatography at the 100 kg/year scale in 100% of cases where input purity was ≤ 1%, compared to about 25% of cases in the dataset as a whole. Finally, we identified a simple factor that strongly predicts phase separation process costs: the mass ratio of reagents versus purified product (the "direct materials usage rate"), which explains up to 58% of variation in cost per unit of purified product among all 290 reports, and up to 98% of variation within particular types of phase separation.

Chemometric Optimization of SPE for the Determination of Multiclass Pesticides in Portable Water Samples by UHPLC-MS/MS

This study aimed on the development of a SPE-UHPLC-MS/MS method for the simultaneous determination of pesticide residues in drinking water samples. A chemometric approach was applied to optimize the efficiency of the SPE pretreatment procedure. This study involved (i) the application of a Full Factorial Design for the screening of the significant factors, (ii) the application of a Central Composite Design for the determination of the optimal conditions and (iii) the evaluation and validation of the significance of the statistically proposed models. Oasis HLB cartridges were used for the extraction. The optimum sample volume was 300 mL and the elution solvent 3 mL of the mixture of methanol:ethylacetate 70:30 v/v. The method was validated according to the international guidelines. Recoveries were ranged from 63 to 116% and the detection limits were between 0.1 and 1.5 pg mL- 1. The validated method could be used in routine analysis for pesticides screening.

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

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

Rapid analysis of insecticidal metabolites from the entomopathogenic fungus Beauveria bassiana 331R using UPLC-Q-Orbitrap MS

Beauveria bassiana, a representative entomopathogenic fungus, is increasingly being utilized as an eco-friendly pest management alternative to chemical insecticides. This fungus produces a range of insecticidal secondary metabolites that act as antimicrobial and immunosuppressive agents. However, detailed qualitative and quantitative analysis related to these compounds remains scarce, we developed a method for the rapid analysis of these metabolites. Eight secondary metabolites (bassianin, bassianolide, beauvericin, beauveriolide I, enniatin A, A1, and B, and tenellin) were efficiently extracted when B. bassiana-infected Tenebrio molitor larvae were ground in 70% EtOH extraction solvent and subsequently subjected to ultrasonic treatment for 30 min. The eight metabolites were rapidly and simultaneously analyzed using ultra-performance liquid chromatography-quadrupole-Orbitrap mass spectrometry (UPLC-Q-Orbitrap MS). Bassianolide (20.6-51.1 µg/g) and beauvericin (63.6-109.8 µg/g) were identified as the main metabolites in B. basssiana-infected larvae, indicating that they are likely major toxins of B. bassiana. Validation of the method exhibited recovery rates in the range of 80-115% and precision in the range of 0.1-8.0%, indicating no significant interference from compounds in the matrix. We developed a method to rapidly analyze eight insecticidal metabolites using UPLC-Q-Orbitrap MS. This can be extensively utilized for detecting and producing insecticidal fungal secondary metabolites.

Polymeric ionic liquid sorbent coatings in thin film microextraction: Insight into sorbent selectivity for pesticides and cannabinoids

Polymeric ionic liquid (PIL) sorbent coatings consisting of polymerizable cations and anions were employed as sorbent coatings in thin film microextraction (TFME) for the extraction of pesticides and cannabinoids. The blades consisted of a thin film of PIL sorbents chemically bonded to vinyltrimethoxysilane-functionalized nitinol sheets. The imidazolium- or ammonium-based PIL sorbents contained aromatic benzyl moieties as well as polar hydroxyl groups or aliphatic functional groups within the chemical structure of the IL monomer. The chemical structure of the IL crosslinkers of the PILs were kept constant across each sorbent, except for the anion, which consisted of either bis[(trifluoromethyl)sulfonyl]imide ([NTf2-]), p-styrenesulfonate ([SS-]), or 3-sulfopropyl acrylate ([SPA-]). Temperature, salt content, and methanol content were optimized as extraction conditions to maximize pesticide-cannabinoid selectivity using Doehlert design of experiments (DOE). Effects of these three factors on selectivity and extraction efficiency are discussed. The optimal extraction conditions consisting of sample temperature (31°C), sodium chloride (30% w/v), and methanol content (0.25% v/v) are compared to initial sorbent screening conditions at a sample temperature of 40°C, 15% (w/v) sodium chloride, and 2.5% (v/v) methanol content. PIL sorbent swelling behavior at different salt and methanol content conditions and its effect on extraction efficiency are hypothesized. Selectivity factors for the sorbents indicated that aromatic moieties within the IL monomer may enhance pesticide-cannabinoid selectivity under optimized conditions, but the extraction efficiency of pesticides that are known to coelute with cannabinoids in the chromatographic separation may be enhanced by employing sorbent coatings with [SPA-] anions.

Design of experiments approach for systematic optimization of a single-shot diaPASEF plasma proteomics workflow applicable for high-throughput

PURPOSE

Plasma is an abundant source of protein biomarkers. Mass spectrometry (MS) is an effective means to measure a large number of proteins in a single run. The recent development of data-independent acquisition with parallel accumulation and serial fragmentation (diaPASEF) on a trapped ion mobility spectrometer (TIMS) affords deep proteomic coverage with short liquid chromatography gradients. In this work, we utilized a process optimization approach, design of experiments (DoE), to maximize precursor identification for a plasma proteomic diaPASEF workflow.

EXPERIMENTAL DESIGN

A partial factorial design was used to screen 11 sample preparation factors and six diaPASEF MS acquisition factors. Selected factors were optimized using the response surface method.

RESULTS

Three important sample preparation factors and the two important MS acquisition factors were identified in the screening experiments and were selected for separate optimization experiments. The optimal parameters were compared to our standard plasma proteomics workflows using either a 1-h or overnight trypsin digestion. The optimized method outperformed the 1-h digestion, and it was similar in performance to the overnight digestion, however, the optimized method could be completed in a day.

CONCLUSION AND CLINICAL RELEVANCE

We have used DoE to report an optimized plasma proteomics workflow for diaPASEF, however, established methods are already highly optimized, and resources may be better spent on running samples than comprehensive optimization.

Precipitation and Extraction Methods for Protein Purification: A Meta-Analysis of Purification Performance and Cost-Effectiveness

For protein drug purification, packed-bed chromatography often remains both the predominant method and a bottleneck for cost and scalability. Accordingly, extensive efforts have been made to develop alternatives, such as precipitation and liquid-liquid extraction. Despite decades of development, such methods have been slow to see adoption in commercial processes. To diagnose the key barriers to implementation and guide future work, we have systematically reviewed studies of protein precipitation and liquid-liquid extraction. We classify the products, methods, and results of 168 publications representing 290 unique purification operations and analyze these operations in terms of both process economics and purification performance. Whereas it is generally assumed that precipitation and extraction methods will have lower costs than chromatography, we find that this is only the case under specific process conditions such as at a large manufacturing scale and low initial sample purity. Furthermore, we find that only a small number of the many precipitation and extraction methods reported to date have shown readiness for implementation in protein drug purification processes. Finally, we identify key factors governing both the economic and purification performance of this class of methods: first, that operating costs are almost entirely predictable by the ratio between the mass of phase-forming materials used and the mass of product protein yielded; second, that use of modern optimization techniques such as Design of Experiments is associated with significantly better purification performance and cost-effectiveness.

Highlights

Alternative separation purification methods are not always cheaper than chromatographyThe use of a combination of phase separating agents remains largely underexplored/underutilizedLower initial purity and increasing production scale favor phase-separation over chromatographyThe direct material usage rate is an important predictor of alternative separation cost-effectivenessCurrent alternative separation method development has largely ignored optimization of direct material usage rate.

Analysis of D-amino acids secreted from murine islets of Langerhans using Marfey's reagent and reversed phase LC-MS/MS

D-amino acids (D-AAs) are important signaling molecules due to their ability to bind ionotropic N-methyl-D-aspartate receptors. D-serine (D-Ser), D-alanine (D-Ala), and D-aspartate (D-Asp) have been found individually in the endocrine portion of the pancreas, the islets of Langerhans, and/or their secretions. However, there has been no report of a comprehensive assessment of D-AAs in islet secretions. To evaluate the release of these compounds, the effectiveness of both 1-(9-fluorenyl)-ethyl chloroformate (FLEC reagent) and 1-fluoro-2,4-dinitrophenyl-5-L-alanine amide (Marfey's reagent, MR) in separation of D/L-AA enantiomeric pairs in islet-specific buffers were evaluated. MR-derivatized D/L AAs showed greater than baseline resolution (Rs ≥ 1.5) of 13 enantiomeric pairs when using a non-linear gradient and an acidic mobile phase system, while FLEC-derivatized AAs exhibited limited resolution on both biphenyl and C18 columns. The optimized MR method yielded highly reproducible separations with retention times less than 1% RSD. Excellent linearity between the analyte concentrations and response (R2 > 0.98) were obtained, with less than 15% RSD for all analyte responses. Most analytes had an LOD at or below 100 nM, except for L-Ala (200 nM). The optimized MR method was used to quantify D-AAs in secretions of 150 murine islets after incubation in 3- and 20-mM glucose. In response to both solutions, D-Ser and D-glutamine were tentatively identified via comparison of retention time and quantifier-to-qualifer ion ratios with standards, and from spiking experiments. Both were secreted in low quantities which did not differ significantly in either low (D-Ser: 44 ± 2 fmol islet-1h-1; D-Gln: 300 ± 100 fmol islet-1h-1) or high (D-Ser: 23 ± 1 fmol islet-1h-1; D-Gln: 120 ± 50 fmol islet-1h-1) glucose across 3 biological replicates. The method developed is robust and can be applied to further examine the release of D-AAs and their potential roles in islet physiology.

The inversion of multiresponse partial least squares models, a useful tool to improve analytical methods in the framework of analytical quality by design

Analytical Quality by Design (AQbD) is the adaptation of Quality by Design (QbD) when it is applied to the development of an analytical method. The main idea is to develop the analytical method in such a way that the desired quality of the Critical Quality Attributes (CQAs), stated via the analytical target profile (ATP), is maintained while allowing some variation in the Control Method Parameters (CMPs). The paper presents a general procedure for selecting factor levels in the CMPs to achieve the desired responses, characterized by the CQAs, when liquid chromatographic methods are to be used for the simultaneous determination of several analytes. In such a case, the CMPs are usually the composition of the ternary mobile phase, its flow rate, column temperature, etc., while typical CQAs refer to the quality of the chromatograms in terms of the resolution between each pair of consecutive peaks, initial and final chromatographic time, etc. The analytical target profile in turn defines the desired characteristics for the CQAs, the reason for the whole approach. The procedure consists of four steps. The first is to construct a D-optimal combined design (mixture-process design) to select the domain and levels of the CMPs. The second step is to fit a PLS2 model to predict the analytical responses expressed in the ATP (the good characteristics of the chromatogram) as a function of the CMPs. The third step is the inversion of the PLS2 model to obtain the conditions necessary to obtain the preset ATP in the corresponding CQAs. The inversion is performed computationally in order to estimate the Pareto front of these responses, namely, a set of experimental conditions to perform the chromatographic determination for which the desired critical quality attributes are met. The fourth final step is to obtain the Method Operable Design Region (MODR), that is, the region where the CMPs can vary while maintaining the quality of the CQAs. The procedure has been applied to some cases involving different analytes, all of which are regulated by the European Union due to their toxicity to human health, namely five bisphenols and ten polycyclic aromatic hydrocarbons.

Laser Sensing and Chemometric Analysis for Rapid Detection of Oregano Fraud

World health is increasingly threatened by the growing number of spice-related food hazards. Further development of reliable methods for rapid, non-targeted identification of counterfeit ingredients within the supply chain is needed. ENEA has developed a portable, user-friendly photoacoustic laser system for food fraud detection, based on a quantum cascade laser and multivariate calibration. Following a study on the authenticity of saffron, the instrument was challenged with a more elusive adulterant, olive leaves in oregano. The results show that the reported method of laser sensing and chemometric analysis was able to detect adulterants at mass ratios of at least 20% in less than five minutes.

Performance of Pristine versus Magnetized Orange Peels Biochar Adapted to Adsorptive Removal of Daunorubicin: Eco-Structuring, Kinetics and Equilibrium Studies

Drugs and pharmaceuticals are an emergent class of aquatic contaminants. The existence of these pollutants in aquatic bodies is currently raising escalating concerns because of their negative impact on the ecosystem. This study investigated the efficacy of two sorbents derived from orange peels (OP) biochar (OPBC) for the removal of the antineoplastic drug daunorubicin (DNB) from pharmaceutical wastewater. The adsorbents included pristine (OPBC) and magnetite (Fe₃O₄)-impregnated (MAG-OPBC) biochars. Waste-derived materials offer a sustainable and cost-effective solution to wastewater bioremediation. The results showed that impregnation with Fe₃O₄ altered the crystallization degree and increased the surface area from 6.99 m²/g in OPBC to 60.76 m²/g in the case of MAG-OPBC. Placket-Burman Design (PBD) was employed to conduct batch adsorption experiments. The removal efficiency of MAG-OPBC (98.51%) was higher compared to OPBC (86.46%). DNB adsorption onto OPBC followed the D-R isotherm, compared to the Langmuir isotherm in the case of MAG-OPBC. The maximum adsorption capacity (q_max) was 172.43 mg/g for MAG-OPBC and 83.75 mg/g for OPBC. The adsorption kinetics for both sorbents fitted well with the pseudo-second-order (PSO) model. The results indicate that MAG-OPBC is a promising adsorbent for treating pharmaceutical wastewater.

Development of a sensitive HPLC method with fluorescence detection for determination of motilin in human plasma

Background: Motilin is a peptide-structured gastrointestinal system hormone. In this study, a sensitive HPLC-fluorescence detection method was developed and validated for the quantification of motilin in human plasma. Materials & methods: Optimization processes were carried out with the experimental design methodology. Analyses were performed on a C8 column (4.6 × 150 mm, 3.5 μm particles) using water and acetonitrile containing trifluoroacetic acid as the mobile phase. Results & conclusion: The method was linear from 2 to 200 ng/ml of motilin. The assay variability was less than 5%. The limit of quantification was found to be 1.84 ng/ml. The applicability of the developed method was successfully demonstrated by quantifying the levels of motilin in human plasma samples.

Development and optimization of stability-indicating method of ethinylestradiol, levonorgestrel, and their main impurities using quality by design approach

The association of Ethinylestradiol 0.03 mg and Levonorgestrel 0.15 mg is a hormonal contraceptive that combines estrogen and progestogen. According to a bibliographic survey, these combined drugs present at least 18 known degradation products, which are required to control the potential impurities harmful to human health. The high number of impurities and the low concentrations of the active pharmaceutical ingredients (APIs) and their respective degradation products increase the complexity of the stability-indicating method development for this medicine. Thus, this work aimed to develop and optimize the stability-indicating method using the quality by design (QbD) approach and in-silico tools for application in samples of oral contraceptives sold in Brazil. The analysis samples were initially subjected to a forced degradation study through 7 days of exposure under acid and alkali hydrolysis, oxidative condition, and oxidation by metal ions. In addition to the chemical exposure, the sample was subjected to physical stress through 10 days of exposure under dry heat, moisture, and photolytic degradation. These exposure samples were analyzed in the development and optimization of chromatographic conditions. As a result, the developed method was able to separate 20 known substances, including the two APIs and their respective 18 degradation products, as well as unknown degradation products obtained by the forced degradation study. Finally, this stability-indicating method was successfully applied for comparative analysis of contraceptive drugs marketed in Brazil, newly purchased and subjected to accelerated stability condition at 40 °C and 75% RH over the 6-month period.

The secret of reversed-phase/weak cation exchange retention mechanisms in mixed-mode liquid chromatography applied for small drug molecule analysis

Resolving complex sample mixtures by liquid chromatography in a single run is challenging. The so-called mixed-mode liquid chromatography (MMLC) which combines several retention mechanisms within a single column, can provide resource-efficient separation of solutes of diverse nature. The Acclaim Mixed-Mode WCX-1 column, encompassing hydrophobic and weak cation exchange interactions, was employed for the analysis of small drug molecules. The stationary phase's interaction abilities were assessed by analysing molecules of different ionisation potentials. Mixed Quantitative Structure-Retention Relationship (QSRR) models were developed for revealing significant experimental parameters (EPs) and molecular features governing molecular retention. According to the plan of Face-Centred Central Composite Design, EPs (column temperature, acetonitrile content, pH and buffer concentration of aqueous mobile phase) variations were included in QSRR modelling. QSRRs were developed upon the whole data set (global model) and upon discrete parts, related to similarly ionized analytes (local models) by applying gradient boosted trees as a regression tool. Root mean squared errors of prediction for global and local QSRR models for cations, anions and neutrals were respectively 0.131; 0.105; 0.102 and 0.042 with the coefficient of determination 0.947; 0.872; 0.954 and 0.996, indicating satisfactory performances of all models, with slightly better accuracy of local ones. The research showed that influences of EPs were dependant on the molecule's ionisation potential. The molecular descriptors highlighted by models pointed out that electrostatic and hydrophobic interactions and hydrogen bonds participate in the retention process. The molecule's conformation significance was evaluated along with the topological relationship between the interaction centres, explicitly determined for each molecular species through local models. All models showed good molecular retention predictability thus showing potential for facilitating the method development.

Performance of global retention models in the optimisation of the chromatographic separation (I): Simple multi-analyte samples

Conventional retention models lead to accurate descriptions of the elution behaviour from the fitting of data for single solutes or from a set of solutes, one by one. However, the simultaneous fitting of several solutes through a regression process that separates the contributions of column and solvent from those of each solute is also possible. The result is a global retention model constituted by a set of equations with some common parameters (those associated with column and solvent), whereas others, specific to each solute, differ for each equation. This work explores the possibilities, advantages, and limitations of global models when they are applied to the optimisation of chromatographic resolution. A set constituted by 13 drugs (diuretics and β-blockers) and a training experimental design of seven multi-linear gradients are considered. Since standards for all compounds were available, the optimisation based on global models could be compared with the conventional optimisation, which is based on individual models. In their current state, global models do not predict changes in elution order, but they do allow for incorporating additional solutes (e.g., new analytes or matrix peaks) with only one new experiment. This possibility is explored by extending the model for the 13 analytes to include 26 peaks associated with a contamination in the injector. The combination of individual and global models allows an optimisation where the effects of matrix peaks on the separation of analytes can be integrated.

A sDOE (Simple Design-of-Experiment) Approach for Parameter Optimization in Mass Spectrometry. Part 1. Parameter Selection and Interference Effects in Top-Down ETD Fragmentation of Proteins in a UHR-QTOF Instrument

Design-of-experiment (DOE) approaches, originally conceived by Fischer, are widely applied in industry, particularly in the context of production for which they have been greatly expended. In a research and development context, DOE can be of great use for method development. Specifically, DOE can greatly speed up instrument parameter optimization by first identifying parameters that are critical to a given outcome, showing parameter interdependency where it occurs and accelerating optimization of said parameters using matrices of experimental conditions. While DOE approaches have been applied in mass spectrometry experiments, they have so far failed to gain widespread adoption. This could be attributed to the fact that DOE can get quite complex and daunting to the everyday user. Here we make the case that a subset of DOE tools, hereafter called SimpleDOE (sDOE), can make DOE accessible and useful to the Mass Spectrometry community at large. We illustrate the progressive gains from a purely manual approach to sDOE through a stepwise optimization of parameters affecting the efficiency of top-down ETD fragmentation of proteins on a high-resolution Q-TOF mass spectrometer, where the aim is to maximize sequence coverage of fragmentation events.

Application of phosphonium deep eutectic solvents as extractants in ultrasound-assisted dispersive liquid-liquid microextraction for preconcentration of trace amounts of herbicides in drainage ditches waters

In this study, an efficient preconcentration method was presented that is based on dispersive liquid-liquid microextraction taking the advantage of newly synthesized phosphonium deep eutectic solvents used as extractants and ultrasound probe as a dispersing agent. The extracts obtained were analyzed by high-performance liquid chromatography. To optimize the five most important factors for the microextraction procedure a central composite design plan was used. Under optimal conditions (140 μl of extractant, 60 mg of NaCl, pH = 2.0, 120 s of extraction time with ultrasound probe as the dispersing agent, 16 min of centrifugation for phase separation), the proposed method allowed to achieve good precision with RSD between 3.2% and 9.7% at 1.0, 5.0 and 40.0 ng ml levels. The preconcentration factors were equal to 42, 39, and 41, and the limits of detection 0.128, 0.103, and 0.135 ng/ml for dicamba, 2-methyl-4-chlorophenoxyacetic acid, and 2-methyl-4-chlorophenoxypropionic acid, respectively. The proposed method was successfully applied for the determination of chlorophenoxy acid herbicides in water samples from drainage ditches with a good recovery in the range of 70%-93%.

User-Driven Strategy for In Silico Screening of Reversed-Phase Liquid Chromatography Conditions for Known Pharmaceutical-Related Small Molecules

In the pharmaceutical field, and more precisely in quality control laboratories, robust liquid chromatographic methods are needed to separate and analyze mixtures of compounds. The development of such chromatographic methods for new mixtures can result in a long and tedious process even while using the design of experiments methodology. However, developments could be accelerated with the help of in silico screening. In this work, the usefulness of a strategy combining response surface methodology (RSM) followed by multicriteria decision analysis (MCDA) applied to predictions from a quantitative structure-retention relationship (QSRR) model is demonstrated. The developed strategy shows that selecting equations for the retention time prediction models based on the pKa of the compound allows flexibility in the models. The MCDA developed is shown to help to make decisions on different criteria while being robust to the user's decision on the weights for each criterion. This strategy is proposed for the screening phase of the method lifecycle. The strategy offers the possibility to the user to select chromatographic conditions based on multiple criteria without being too sensitive to the importance given to them. The conditions with the highest desirability are defined as the starting point for further optimization steps.

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

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

Design of experiment techniques for the optimization of chromatographic analysis conditions: A review

Design of experiment (DoE) techniques have been widely used in the field of chromatographic parameters optimization as a valuable tool. A systematic literature review of the available DoE techniques applied to the development of a chromatographic analysis method is presented in this paper. First, the most common available designs and the implementation steps of DoE are comprehensively introduced. Then the studies in recent 10 years for the application of DoE techniques in various chromatographic techniques are discussed, such as capillary electrophoresis, liquid chromatography, gas chromatography, thin-layer chromatography, and high-speed countercurrent chromatography. Current problems and future outlooks are finally given to provide a certain inspiration of research in the application of DoE techniques to the different chromatographic techniques field. This review contributes to a better understanding of the DoE techniques for the efficient optimization of chromatographic analysis conditions, especially for the analysis of complex systems, such as multicomponent drugs and natural products.

Implementation of QbD Approach to the Development of Chromatographic Methods for the Determination of Complete Impurity Profile of Substance on the Preclinical and Clinical Step of Drug Discovery Studies

The purpose of this work was to demonstrate the use of the AQbD with the DOE approach to the methodical step-by-step development of a UHPLC method for the quantitative determination of the impurity profile of new CPL409116 substance (JAK/ROCK inhibitor) on the preclinical and clinical step of drug discovery studies. The critical method parameters (CMPs) have been tested extensively: the kind of stationary phase (8 different columns), pH of the aqueous mobile phase (2.6, 3.2, 4.0, 6.8), and start (20–25%) and stop (85–90%) percentage of organic mobile phase (ACN). The critical method attributes (CMAs) are the resolution between the peaks (≥2.0) and peak symmetry of analytes (≥0.8 and ≤1.8). In the screening step, the effects of different levels of CMPs on the CMAs were evaluated based on a full fractional design 22. The robustness tests were established from the knowledge space of the screening step and performed by application fractional factorial design 2(4−1). Method operable design region (MODR) was generated. The probability of meeting the specifications for the CMAs was calculated by Monte-Carlo simulations. In relation to literature such a complete AQbD approach including screening, optimization, and validation steps for the development of a new method for the quantitative determination of the full profile of nine impurities of an innovative pharmaceutical substance with the structure-based pre-development pointed out the novelty of our work. The final working conditions were as follows: column Zorbax Eclipse Plus C18, aqueous mobile phase 10 mM ± 1 mM aqueous solution of HCOOH, pH 2.6, 20% ± 1% of ACN at the start and 85% ± 1% of ACN at the end of the gradient, and column temperature 30 °C ± 2 °C. The method was validated in compliance with ICH guideline Q2(R1). The optimized method is specified, linear, precise, and robust. LOQ is on the reporting threshold level of 0.05% and LOD at 0.02% for all impurities.

An Effective Shrinkage Control Method for Tooth Profile Accuracy Improvement of Micro-Injection-Molded Small-Module Plastic Gears

An effective method to control the non-linear shrinkage of micro-injection molded small-module plastic gears by combining multi-objective optimization with Moldflow simulation is proposed. The accuracy of the simulation model was verified in a micro-injection molding experiment using reference process parameters. The maximum shrinkage (Y1), volume shrinkage (Y2), addendum diameter shrinkage (Y3), and root circle diameter shrinkage (Y4) were utilized as optimization objectives to characterize the non-linear shrinkage of the studied gear. An analysis of the relationship between key process parameters and the optimization objectives was undertaken using a second-order response surface model (RSM-Quadratic). Finally, multi-objective optimization was carried out using the non-dominated sorting genetic algorithm-II (NSGA-II). The error rates for the key shrinkage dimensions were all below 2%. The simulation results showed that the gear shrinkage variables, Y1, Y2, Y3, and Y4, were reduced by 5.60%, 8.23%, 11.71%, and 11.39%, respectively. Moreover, the tooth profile inclination deviation (fHαT), the profile deviation (ffαT), and the total tooth profile deviation (FαT) were reduced by 47.57%, 23.43%, and 49.96%, respectively. Consequently, the proposed method has considerable potential for application in the high-precision and high-efficiency manufacture of small-module plastic gears.

Optimization and troubleshooting of preparative liquid chromatography using statistical design of experiments: Four small-molecule case studies

Statistical design of experiments (DoE) is used to aid in the development and execution of preparative liquid chromatography (LC) for large-scale purification of active pharmaceutical ingredients (API) and pharmaceutical intermediates. Four purification case studies were undertaken. In case study 1, a normal phase preparative silica method is developed and modeled. After initial method screening, DoE results were used to set mobile phase composition, flowrate, and sample diluent. Of the three particle sizes studied (10 µm, 20 µm, 50 µm) only 10 µm silica resin was able to produce purified API at the yield (>96%) and productivity (> 1 kg/kg-resin/day) necessitated by the project. The second case study uses DoE studies to identify critical process parameters of column load, mobile phase solvent ratio and basic modifier level for a low-resolution, preparative, chiral separation. Trade-offs between purity, yield and productivity are quantified in a tight separation which made compromising on process outcomes a necessity. The third case study troubleshoots a loss of yield experienced during operation of a process-scale reverse-phase LC purification. DoE is used to identify a critical interaction between levels of acetonitrile and phosphoric acid in the mobile phase. An operating region which increased yield from around 85% to 97% was defined and implemented. The fourth case study was initially designed as a preparative chromatography purification of API. DoE was used to screen mobile phase solubility. These experiments uncovered conditions where API is soluble, and impurities are not. The solubility model in acetonitrile/water mixtures is further defined via a response surface DoE. The resulting targeted solvent mixture allows bulk purification via dissolution of API while three less-polar impurities remain in the solid phase and are removed by filtration. These four case studies demonstrate the efficiency of DoE and response surface modeling as tools for process development and optimization.

An Experimental and Modeling Combined Approach in Preparative Hydrophobic Interaction Chromatography

Chromatography is a technique widely used in the purification of biopharmaceuticals, and generally consists of several chromatographic steps. In this work, Hydrophobic Interaction Chromatography (HIC) is investigated as a polishing step for the purification of therapeutic proteins. Adsorption mechanisms in hydrophobic interaction chromatography are still not completely clear and a limited amount of published data is available. In addition to new data on adsorption isotherms for some proteins (obtained both by high-throughput and frontal analysis method), and a comparison of different models proposed in the literature, two different approaches are compared in this work to investigate HIC. The predictive approach exploits an in-house code that simulates the behavior of the component in the column using the model parameters found from the fitting of experimental data. The estimation approach, on the other hand, exploits commercial software in which the model parameters are found by the fitting of a few experimental chromatograms. The two approaches are validated on some bind-elute runs: the predictive approach is very informative, but the experimental effort needed is high; the estimation approach is more effective, but the knowledge gained is lower. The second approach is also applied to an in-development industrial purification process and successfully resulted in predicting the behavior of the system, allowing for optimization with a reduction in the time and amount of sample needed.

The Design of Experiment as a Tool to Model Plant Trace-Metal Bioindication Abilities

Bioindicator plants are species that have the capacity to linearly uptake some elements (metal and metalloids) from the growing substrate, thus reflecting their concentration in the soil. Many factors can influence the uptake of these elements by plants, among which is the simultaneous presence of several metals, a common situation in contaminated or natural soils. A novel approach that can be used to validate the bioindication ability of a species growing on a polymetallic substrate is the design of experiment (DoE) approach. The aim of the present study was to apply the DoE in full factorial mode to model the Cu, Cd, Pb, Zn, and Cr bioindication capacity of Polygonum aviculare, used as the model plant. The results showed that P. aviculare has the ability to bioindicate Cd and Cr with a linear uptake (from 0.35 to 6.66, and 0.1 to 3.4 mg kg-1, respectively) unaffected by the presence of other metals. Conversely, the uptake of Pb, Cu, and Zn is strongly influenced by the presence of all the studied metals, making their concentration in the plant shoot not proportional to that of the soil. In conclusion, these preliminary results confirmed that the DoE can be used to predict the bioindicator abilities of a plant for several elements at the same time and to evaluate the interactions that can be established between variables in the growing medium and in the plant itself. However, more studies including other plant species are needed to confirm the effectiveness of this method.

Ultrasound-assisted cloud point microextraction of certain preservatives in real samples and determination by HPLC

Ultrasound-assisted cloud point microextraction (UA-CPME) was performed for certain preservatives (p-hydroxy benzoic acid and its alkyl esters, methyl, ethyl, propyl and butyl parabens). Then, an HPLC method was developed for their simultaneous determination in pharmaceutical and cosmetic samples. The chromatograms of these substances were recorded on a C18 column using a gradient elution technique with various solvent systems at different flow rates and at 254 nm wavelength using a diode-array detector (DAD). The analysis conditions found by the classical method were optimized using the Box-Behnken design (BBD). In the design, the effect of each factor was examined with 3 and 4 factors for UA-CPME and HPLC analyses, respectively. The brij 58 concentration (BC), Na₂SO₄ amount (SA) and extraction time (ET) for UA-CPME, and the mobile phase 1 (MP1) ratio, mobile phase 2 (MP2) ratio, flow rate (FR) and column temperature parameters for HPLC analysis were obtained for the investigated levels. The factors affecting the resolution were determined by applying regression analysis to the experimental results. The analysis of variance (ANOVA) test was applied to ensure result reliability. The ANOVA test was used to determine the reliability of the results. A model was created with the obtained data. The developed method was validated by examining linearity, reproducibility, accuracy, limit of quantification and limit of the detection. Methyl paraben (with 0.148% RSD value and 0.060% relative error), and propyl paraben (with 0.149% RSD value and 0.120% relative error) were determined in the syrup sample by the developed method. Methyl paraben with recovery values of (98.32-99.42)% and ethyl paraben with recovery values of (99.17-99.41)%, were determined in a hand cream.

HPLC method with post-column derivatization for the analysis of endogenous histidine in human saliva validated using the total-error concept

Histidine (His) is an essential amino acid that plays an important biological role and associated with various pathological conditions. A simple and reliable method for the determination of endogenous histidine in human saliva was optimized and validated. The analyte was separated from the saliva matrix by cation exchange chromatography and detected fluorimetrically (λ_ex/λ_em = 360/440 nm) after online, specific post-column derivatization (PCD) reaction with o-phthalaldehyde. The chemical and instrumental variables of the post-column reaction were optimized using Box-Behnken experimental design to achieve maximum sensitivity. Method validation was carried out employing the total-error concept. Histidine could be analyzed reliably in the range of 0.5-5.0 μΜ, with an LOD (S/N = 3) of 50 nM. Monte Carlo simulations and capability analysis were used to investigate the ruggedness of the PCD reaction. The sampling strategy, sample preparation and stability were also investigated. Seventeen saliva samples were successfully analyzed with histidine levels being in the range of 2.7-19.5 μΜ.

Fractional Factorial Design Study for the Extraction of Cannabinoids from CBD-Dominant Cannabis Flowers by Supercritical Carbon Dioxide

The optimization of the supercritical fluid extraction (SFE) of cannabinoids, using supercritical carbon dioxide (scCO2), was investigated in a fractional factorial design study. It is hypothesized that four main parameters (temperature, pressure, dry flower weight, and extraction time) play an important role. Therefore, these parameters were screened at predetermined low, medium, and high relative levels. The density of scCO2 was used as a factor for the extraction of cannabinoids by changing the pressure and temperature. The robustness of the mathematical model was also evaluated by regression analysis. The quantification of major (cannabidiol (CBD), cannabidiolic acid (CBDA), delta 9-tetrahydrocannabinol (Δ9-THC), delta 8-tetrahydrocannabinol (Δ8-THC), and delta 9-tetrahydrocannabinol acid (THCA-A)) and minor (cannabidivann (CBDV), tetrahydrocannabivann (THCV), cannabigerolic acid (CBG), cannabigerol (CBGA), cannabinol (CBN), and cannabichomere (CBC)) cannabinoids in the scCO2 extract was performed by RP-HPLC analysis. From the model response, it was identified that long extraction time is a significant parameter to obtain a high yield of cannabinoids in the scCO2 extract. Higher relative concentrations of CBD(A) (0.78 and 2.41% w/w, respectively) and THC(A) (0.084 and 0.048% w/w, respectively) were found when extraction was performed at high relative pressures and temperatures (250 bar and 45 °C). The higher yield of CBD(A) compared to THC(A) can be attributed to the extract being a CBD-dominant cannabis strain. The study revealed that conventional organic solvent extraction, e.g., ethanol gives a marginally higher yield of cannabinoids from the extract compared to scCO2 extraction. However, scCO2 extraction generates a cleaner (chlorophyll-free) and organic solvent-free extract, which requires less downstream processing, such as purification from waxes and chlorophyll.

Protein Hydrolysis by Subcritical Water: A New Perspective on Obtaining Bioactive Peptides

The importance of bioactive peptides lies in their diverse applications in the pharmaceutical and food industries. In addition, they have been projected as allies in the control and prevention of certain diseases due to their associated antioxidant, antihypertensive, or hypoglycemic activities, just to mention a few. Obtaining these peptides has been performed traditionally by fermentation processes or enzymatic hydrolysis. In recent years, the use of supercritical fluid technology, specifically subcritical water (SW), has been positioned as an efficient and sustainable alternative to obtain peptides from various protein sources. This review presents and discusses updated research reports on the use of subcritical water to obtain bioactive peptides, its hydrolysis mechanism, and the experimental designs used for the study of effects from factors involved in the hydrolysis process. The aim was to promote obtaining peptides by green technology and to clarify perspectives that still need to be explored in the use of subcritical water in protein hydrolysis.

Optimization and Evaluation of the In Vitro Permeation Parameters of Topical Products with Non-Steroidal Anti-Inflammatory Drugs through Strat-M® Membrane

Pharmaceutical products containing non-steroidal anti-inflammatory drugs (NSAIDs) are among the most prescribed topical formulations used for analgesic and antirheumatic properties. These drugs must overcome the skin barrier to cause a therapeutic effect. Human skin has been widely used as a model to study in vitro drug diffusion and permeation, however, it suffers from many limitations. Therefore, to perform in vitro permeation test (IVPT), we used a Strat-M® membrane with diffusion characteristics well-correlated to human skin. This study's objective was to optimize the IVPT conditions using Plackett-Burman experimental design for bio-predictive evaluation of the in vitro permeation rates of five non-steroidal anti-inflammatory drugs (diclofenac, etofenamate, ibuprofen, ketoprofen, naproxen) across Strat-M® membrane from commercial topical formulations. The Plackett-Burman factorial design was used to screen the effect of seven factors in eight runs with one additional center point. This tool allowed us to set the sensitive and discriminative IVPT final conditions that can appropriately characterize the NSAIDs formulations. The permeation rate of etofenamate (ETF) across the Strat-M® membrane was 1.7-14.8 times faster than other NSAIDs from selected semisolids but 1.6 times slower than the ETF spray formulation.

Robust optimization of SWATH-MS workflow for human blood serum proteome analysis using a quality by design approach

Background

It is not enough to optimize proteomics assays. It is critical those assays are robust to operating conditions. Without robust assays, proteomic biomarkers are unlikely to translate readily into the clinic. This study outlines a structured approach to the identification of a robust operating window for proteomics assays and applies that method to Sequential Window Acquisition of all Theoretical Spectra Mass Spectroscopy (SWATH-MS).

Methods

We used a sequential quality by design approach exploiting a fractional screening design to first identify critical SWATH-MS parameters, then using response surface methods to identify a robust operating window with good reproducibility, before validating those settings in a separate validation study.

Results

The screening experiment identified two critical SWATH-MS parameters. We modelled the number of proteins and reproducibility as a function of those parameters identifying an operating window permitting robust maximization of the number of proteins quantified in human serum. In a separate validation study, these settings were shown to give good proteome-wide coverage and high quantification reproducibility.

Conclusions

Using design of experiments permits identification of a robust operating window for SWATH-MS. The method gives a good understanding of proteomics assays and greater data-driven confidence in SWATH-MS performance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-021-09323-z.

Testing experimental designs in liquid chromatography (II): Influence of the design geometry on the prediction performance of retention models

In liquid chromatography, the reliability of predictions carried out with retention models depends critically on the quality of the training experimental design. The search of the best design is more complex when gradient runs are used instead of isocratic experiments. In Part I of this work (JCA 1624 (2020) 461180), a general methodology based on the error propagation theory was developed and validated for assessing the quality of training designs involving gradients. The treatment relates the mathematical properties of a retention model with the geometry of the training designs and their subsequent predictions. In that work, only five usual designs were considered. Part II investigates in detail the effects on predictions when the features of the training design (number and distribution of the experiments, initial and final modifier content, gradient slope(s), and location of gradient nodes and pulses) are varied systematically. Several groups of related designs containing one or more isocratic steps, linear or multi-linear gradients, or mixed isocratic/gradient runs, among others (in total 38 designs) were evaluated. Box and whiskers and triple plots of expected relative uncertainties were used to evidence the differences in prediction performance. The purpose was to give recommendations to construct designs with good prediction performance. The best designs sample (considering all runs) concentrations as diverse as possible, at any gradient time.