Semaglutide and liraglutide are long-acting glucagon-like peptide-1 receptor agonists used to treat type-2 diabetes and obesity. Recent advances in peptide synthesis and analytical technologies have enabled the development of synthetic generic peptide for reference listed drugs (RLD) originating from recombinant DNA (rDNA) technology. Since the original semaglutide and liraglutide were produced through rDNA technology, there has been great interest in developing their synthetic peptides as generic versions of the original drugs. Therefore, this study aimed to develop a peptide mapping method to describe the primary structure of semaglutide and liraglutide using ultra-performance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS), and to apply this method to demonstrate the sameness between synthetic peptides for generic drugs and rDNA peptides of the original drugs. Masses of the peptide fragments were identified using HRMS at an accurate level of mass error below 10 ppm, and their sequences were determined via MS sequencing using in-source fragmentation, which was also useful for identifying the fatty acid chain modification site. Full sequence coverage of each semaglutide and liraglutide was accomplished by combining peptide maps generated using Glu-C and chymotrypsin. The proposed peptide mapping method using UPLC-HRMS was useful for determining active ingredient sameness between generic synthetic peptides and previously approved peptide drug products of rDNA origin.

Accurate measurement of serum parathyroid hormone (PTH) is crucial for diagnosing and managing endocrine and osteological diseases. Conventional immunoassay methods struggle with cross reactivity issues between full-length PTH and truncated fragments or post-translationally modified forms. Both the standardization of PTH assays and the peptide's stability are concerning. This study addresses these issues by establishing an immunocapture coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to precisely quantify PTH1-84. PTH1-84 was isolated from one mL serum samples by immunocapture on a polystyrene bead and eluted from matrix, then quantitated by LC-MS/MS. The results from 268 serum samples were compared to an intact PTH immunoassay. The assay's linear range was 5.0-1000.0 pg/mL. The intra-assay coefficients of variation (CVs) ranged from 3.2 % to 6.8 %, and the inter-assay CVs ranged from 4.6 % to 9.5 %. The extraction efficiencies were 98.0 %-100.5 %, with no significant matrix effects observed after internal standard correction. The correlation coefficient between LC-MS/MS and immunoassay was 0.989, but the bias between the methods was substantial. Nevertheless, the immunocapture purification coupled LC-MS/MS method offers a promising approach for accurate PTH measurement.

Medicinal and aromatic plants are alternative products to synthetics because of their antioxidant, antimicrobial, anti-inflammatory and antidiabetic effects. The objective of this study is to investigate the automated solvent extraction (ASE) process parameters for the extraction of bioactive-rich substances from purple basil (Ocimum basilicum L.). Process optimization in relation to total phenolic content (TPC), total flavonoid content (TFC), and total anthocyanin content (TAC) was performed through a chemometric approach. The ASE system was designed, modelled and optimized by 3-factor and 3-level Box-Behnken design of Response Surface method (RSM). Antioxidant activity of the samples were measured by 2 different free radical scavenging activity assays (ABTS and DPPH). By using principal component analysis (PCA) to the dataset, the impact of interactions between the parameters was also evaluated according to their antioxidant activity, TPC, TFC and TAC levels. The optimal ASE conditions (0.3 g of purple basil, 19 min of immersion time and 66 % ethanol solution) provided the highest yields of TPC (98.888 mg-GAE/g-DM), TFC (27.033 mg-CE/g-DM) and TAC (11.556 mg-C3G/g-DM), which were verified by satisfactory validation findings (the error<2 %).

Oxidative stress (OS) arises mainly from exposure to reactive oxygen species (ROS) such as superoxide anion, hydroxyl radical, and hydrogen peroxide. These molecules can cause significant damage to proteins, DNA, and lipids, leading to various diseases. Cells fight ROS with detoxifying enzymes; however, an imbalance can cause damage leading to ischemic conditions, heart disease progression, and neurological disorders such as Alzheimer's disease. Accurate assessment of OS levels is then crucial and oxidized lipidic products are considered relevant OS biomarkers. In fact, lipids are particularly prone to ROS attack, leading to lipid peroxidation, cell membrane damage, and toxic by-products affecting DNA, proteins, and low-density lipoproteins. This review reports on recent advances in LC-MS/MS approaches for OS lipidic biomarkers, focusing on overcoming analytical challenges. 3 different classes of biomarkers have been reported, malondialdehyde, isoprostanes and oxidised sterols. For each class, the main analytical challenges with a particular focus on derivatisation procedure, sensitivity, matrix effect, ionisation have been described and discussed. The recent advancements of the LC-MS-MS procedures move towards simpler approaches, reducing errors and improving the reliability of the measurement thus enabling a comprehensive and robust OS assessment.

Acetylcholinesterase (AChE) is widely recognized as a promising therapeutic target enzyme for Alzheimer's disease (AD). The screening of AChE inhibitors (AChEIs) holds great significance for the treatment of AD. In this study, cellulose filter paper (CFP) -immobilized AChE was prepared and firstly applied to screening AChEIs from 30 % ethanol extract of Phyllanthus emblica L. fruits combined with ultra-high performance liquid chromatography quadrupole time-of-fight mass spectrometry (UHPLC-Q-TOF-MS/MS). Using CFP-immobilized AChE as the bait, AChEIs were harvested and the instantaneous separation characteristics of CFP were utilized to further facilitate the separation of the complex from the inactive components. Ultimately, 27 compounds specifically bound with AChE were screened and identified using UHPLC-Q-TOF-MS/MS. Additionally, molecular docking was employed to explore the binding mechanisms between screened potential inhibitors and AChE. The results show that, most of the screened compounds were found to exhibit higher affinity that of the positive control (huperzine A), and all the compounds expect mucic acid to be well embedded into the active pocket of AChE. To verify the reliability of the screening method and molecular docking, two commercial standards geraniin and ellagic acid were experimented with an AChE inhibition assay in vitro. The results showed that both compounds were found to effectively inhibit AChE with IC values of 42.42 ± 7.10 μM, 172.43 ± 9.22 μM. The developed method exhibits the advantages of rapidness and effectiveness in screening of AChEIs from complex herbal extracts.

Wastewater-based epidemiology (WBE) offers a promising approach by providing objective data on antipsychotic drug consumption within a population that can be used to monitor abuse, misuse, and regional prescription patterns. However, accurate estimations depend on knowing the stability of drug biomarkers. This study provides a comprehensive analysis of the stability of 11 antipsychotic biomarkers (parent drugs and their metabolites) in influent wastewater, using a series of experiments mimicking in-sewer transport (in-sewer setup and deconjugation) and in-sample stability (benchtop, frozen cartridge, long-term sample storage, and freeze-thaw). In-sample stability experiments are exposed to various conditions (i.e., filtration, acidification) commonly used for storage. The results reveal compound-specific stability profiles, with quetiapine showing notable high stability across most experiments. In contrast, N-desmethylolanzapine and dehydroaripiprazole demonstrated rapid degradation. Acidification before storage led to significant degradation of some compounds, decreasing the accuracy of WBE consumption estimates and rendering it unsuitable as a sample storage method. Overall, the study found that compound-specific degradation patterns underscore the necessity for tailored analytical approaches when using WBE to monitor antipsychotic drug use. Future research should focus on bioreactor studies mimicking in-sewer conditions and the application of correction factors to enhance the accuracy of consumption estimates, facilitating more reliable public health surveillance through WBE.

Trametes robiniophila Murr. (Huaier) is a traditional medicinal fungus known for its pharmacological properties, including heat-clearing, detoxifying, anti-inflammatory, and antitumor effects. Our previous research has demonstrated its antiviral activity, but the exact therapeutic mechanisms remain unclear. This study aims to explore the mechanisms of 50 % methanol extract of Huaier (HME) in treating influenza using 16S rRNA high-throughput sequencing and metabolomics techniques. The results showed that the HME significantly reduced the lung index and viral load in the lungs of influenza-infected mice, alleviated pathological damage in lung tissues, and downregulated the expression levels of inflammatory cytokines Interleukin-6 (IL-6), Tumor Necrosis Factor-α (TNF-α) and Interferon-γ (IFN-γ) in lung tissues. Furthermore, the HME enhanced the diversity of gut microbiota in infected mice, significantly increasing the relative abundance of beneficial bacteria, such as Alistipes and Alloprevotella. Through non-targeted metabolomic analysis of mouse feces, 45 potential biomarkers were identified. Meanwhile, the low-dose of HME was able to restore the disrupted metabolic levels. Analysis of gut microbiota and biomarker pathways revealed that HME primarily affects nicotinate and nicotinamide metabolism, which may be the key mechanism for its intervention in influenza. In addition, Spearman correlation analysis showed that most biomarkers were significantly associated with pharmacodynamics and the Alloprevotella.

The aim of this work was to develop and validate a rapid dispersive-solid-phase extraction method for the quantification of pyrrolizidine alkaloids (PA) from plant extracts. The method was focused on the significant removal of the intricate matrix to ensure good sensitivity for the subsequent instrumental analysis of PA. This was achieved by employing nano-zirconium silicate (NZS) as a dispersive-SPE sorbent. The specific affinity of NZS for PAs allowed for the effective removal of a substantial portion of the complex matrix, thereby significantly improving the sensitivity of the method, compared to the common methods, were no specific enrichment of the PAs on the SPE sorbent is achieved. Ultra-high-performance liquid chromatography coupled to high resolution time-of-flight mass spectrometry (UHPLC/TOF MS) was used for the qualitative and quantitative analysis of PA. The procedure demonstrated high recoveries for the standard compounds spiked into a blank verbena extract at different concentrations. Recovery rates of 72-95 % for PA, and 30-70 % for their respective N-oxides (PANO) could be obtained. The method was compared to the most commonly used C18 SPE sorbent, and demonstrated a significant lower limit of quantification (LOQ) of 0.64-4.5 ng mL as compared to 4.98-25.7 ng mL. The method was validated in accordance with ICH guidelines. PA standards had a linear response between 5 and 150 ng mL and demonstrated a co-efficient of variance below ± 3 % with a % relative error below ± 15. The presented analytical approach was also tested for the determination of PA from contaminated Verbenae herba extract with success. The presented scheme improves the clean-up efficacy of the already used stationary phases for PA analysis and provides a great alternative analytical tool for the isolation of PAs from plant extracts.

The dynamic landscape of mRNA technology highlights the need for innovative quality control (QC) strategies. In this study, we described an efficient one-step digestion approach for concurrent generation of 5'- and 3'-end fragments, enabling simultaneous mRNA capping and poly(A) tail analysis. Tailored 10-23-type DNAzymes, designed from 5'- and 3'-Untranslated Regions (UTRs), selectively cleaved mRNA to release both the 5'-Capped or uncapped short fragments and 3'-Poly(A) tail cleavage products. Polyacrylamide gel electrophoresis (PAGE) and ion pair reversed-phase liquid chromatography (IP-RP LC) analyses confirmed the production of 5'- and 3'-cleavage fragments in a single-step reaction, and LC-mass spectrometry (LC MS) validated these findings. The DNAzyme-mediated cleavage offers notable advantages over other assays for mRNA cap and tail characterization. Direct and simultaneous analysis of both capping efficiency and poly(A) tail length post-cleavage by DNAzymes, without additional purification steps and costly MS analysis, markedly streamlines the sample preparation and analysis process, making it highly suitable for QC testing.

In recent years, metabolite identification of chemical constituents of traditional Chinese medicine (TCM) has been extensively studied. However, due to the intricacy of metabolic processes and the low concentration of metabolites, identifying metabolites of TCM in vivo is still a tough work. Meanwhile, credibility of metabolite identification through mass spectrum technology has been called into question by reason of the lack of metabolite standards. In this study, ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS) was used to detect biological samples including plasma, feces, urine, liver, kidney, brain of normal and middle cerebral artery occlusion (MCAO) rats orally administrated water extract of Danshen-Honghua herbal pair (DHHP). An analysis strategy which combined MS data analysis platform UNIFI with quantitative structure-retention relationship (QSRR) model was established. First, metabolites of DHHP were identified rapidly by utilizing UNIFI analysis platform to analyze acquired MS data. Then, quantitative structure-retention relationships model was built through BP neural network optimized by the ant colony algorithm. Finally, predicted retention times of identified metabolites were produced by QSRR model. Metabolites identified by UNIFI whose difference between predicted and experimental retention time was beyond 1 min were considered false positive and excluded to improve the credibility of identification. According to the established analysis strategy, 26 prototypes and 16 metabolites were identified. Established MS data analysis strategy which combined UNIFI analysis platform with QSRR model was proven to be a creditable method to identify the in vivo metabolites of TCM rapidly and accurately.

Bile acids (BAs) are essential signaling molecules that engage in host and gut microbial metabolism, playing a crucial role in maintaining organismal stability. Liquid chromatography-mass spectrometry (LC-MS) is a widely employed technique for metabolite analysis in biological samples due to its high sensitivity, excellent specificity, and low detection limits. This method has emerged as the mainstream approach for the detection and analysis of BAs. Pseudo-targeted analysis combines the advantages of both untargeted and targeted metabolomics methodologies. In this study, we developed a comprehensive and rapid method for detecting and analyzing BAs using LC-MS technology, applied to liver samples from bile duct-ligated (BDL) mice exhibiting liver fibrosis. A self-constructed database containing 488 BAs was established, and raw data from universal metabolome standard (UMS) were acquired using UHPLC-Q/TOF-MS. A total of 172 BA compounds were characterized, including 74 free BAs and 158 BAs were successfully detected using the high-coverage assay established with UHPLC-QQQ-MS. This assay was employed in the BDL liver fibrosis mouse model, where statistical analysis tools identified 20 differential BAs in the livers of affected mice. The development of this rapid method signifies a substantial advancement in the field, illustrating its utility in identifying differential BAs and enhancing our understanding of liver fibrosis. Furthermore, the high-coverage assay's ability to accurately analyze a diverse range of BAs could substantially aid in diagnosing and treating liver diseases.

Minocycline is an antibiotic of the tetracycline family which is widely used to treat a range of medical conditions. Although it has been in use for more than 50 years, little information is available on its metabolism in the human body. In this study, we simulate the biotransformation of minocycline by means of electrochemistry coupled to mass spectrometry. This analytical technique has already been used successfully in several cases to imitate enzyme-catalyzed reactions. Using this approach, we could show the generation of multiple electrochemical oxidation products which were characterized by tandem mass spectrometry. A N-dealkylated product was found to correspond to a literature-known in vivo metabolite. Two further oxidation products were detected, one of which exhibiting a reactive quinone moiety formed through electrochemical oxidation. The reactivity of this transformation product was assessed by conjugation reactions with glutathione, human hemoglobin and human serum albumin as model biomolecules. For all three peptides, conjugation reactions took place within minutes, corresponding to the number of free cysteine residues in the respective molecule, which are particularly susceptible to electrophiles like quinones. For glutathione, serum albumin and α-hemoglobin, a single conjugation of the reactive transformation product took place, whereas a twofold conjugation was detected for β-hemoglobin. This project showcases the capability of the purely instrumental approach to simulate the metabolism of xenobiotics without an interfering matrix to screen for reactive transformation products and to assess the reactivity of these products with regard to biomolecules.

Isothermal, enzyme-free amplification techniques, such as the hybridization chain reaction (HCR) and catalytic hairpin assembly (CHA), have gained significant attention for mRNA analysis. Despite their potential, these methods still face challenges, including false positives and low amplification efficiency. To overcome these limitations, we have developed a confined catalytic hairpin assembly and hybridization chain reaction (CHA-HCR) system that utilizes cholesterol-modified hairpin probes to enhance the sensitivity and specificity of mRNA detection. This system integrates cholesterol-modified hairpin probes (CHA probes) with hybridization chain reaction probes (HCR probes), leveraging hydrophobicity-mediated assembly to create a robust biosensing platform. The CHA-HCR system initiates a complex formation with the target mRNA, triggering a cascade of hybridization events that amplify the fluorescence signal. Employing ANXA2 mRNA as a model system, our results reveal that the CHA-HCR system achieves a detection limit (LOD) of 8.7 pM and offers high selectivity, effectively distinguishing ANXA2 mRNA from similar RNAs with single-base mismatches. Additionally, the CHA-HCR probes demonstrate stable detection performance in complex environments and exhibit excellent sensing capabilities in clinical tissue samples, successfully differentiating ANXA2 mRNA expression between leiomyoma and adenomyosis patient tissues. This study introduces a promising approach for the early diagnosis and monitoring of diseases associated with mRNA, potentially contributing to improved clinical outcomes and personalized treatment strategies.

Alkaptonuria (AKU) is a rare autosomal-recessive disease which is characterized through black urine and ochronosis. It is caused by deficiency of the enzyme Homogentisate 1,2-dioxygenase in the Phenylalanine/Tyrosine degradation pathway which leads to the accumulation of Homogentisic acid (HGA). Urine was provided by AKU patients and healthy controls. Several different methods were developed in this study each with a specific goal. Firstly, a simple and inexpensive RP-UHPLC-UV method for routine monitoring of HGA as a key metabolite employing a Phenylhexyl stationary phase chemistry. Validation was performed in accordance to FDA guidelines and method selectivity was further evaluated via on-line high-resolution sampling 2D-LC-QToF-MS, coupling the Phenylhexyl phase in the first dimension with a C18 phase in the second dimension. Secondly, a targeted and accurate RP-UHPLC-MRM-QTRAP assay, providing quantitative analysis of the relevant pathway metabolites based on a Phenylhexyl stationary phase, and lastly an untargeted HILIC-UHPLC-QToF-MS/MS method with SWATH (sequential window acquisition of all theoretical mass spectra) acquisition employing a sulfobetaine-type HILIC-Z superficially porous particle column, with the aim of uncovering more details about the metabolic profile of this genetic disorder. By untargeted analysis 204 metabolites could be detected and annotated in positive and negative ESI mode in total. Two separate LC methods were employed, differing in their conditions depending on the ionization mode (20 mM ammonium formate as buffer additive adjusted to a pH = 3.5 with formic acid in ESI mode and 20 mM ammonium acetate adjusted to a pH = 7.5 with acetic acid in ESI mode). By effectively combining the aforementioned methods, a comprehensive workflow was developed, allowing the effective analysis of both patient and control urine samples.

The incidence of Parkinson's disease (PD) increases with age. Previous pharmacological studies have shown the potential of Huatan Jieyu Granules (HGs) for the treatment of PD, but the exact mechanisms remain unclear. This study aimed to explore the effects of herbal treatment on PD using mouse models and single-cell sequencing.

The incidence of acute liver injury is increasing and poses a significant threat to human health. Ganoderma lucidum spore oil (GLSO), a lipid substance extracted from Ganoderma lucidum spore powder using supercritical CO technology, has been investigated for its potential to prevent acute liver injury. However, the specific mechanism underlying the protective effects of GLSO remains incompletely understood. In this study, we investigated the preventive effect of GLSO on acute liver injury in rats, focusing on the gut microbiome and serum metabolomics. GLSO effectively alleviated liver dysfunction and reduced inflammation, leading to the prevention of acute liver injury in rats. Serum metabolomics analysis revealed that GLSO primarily modulated lipid metabolic pathways related to glycerophospholipid metabolism and sphingolipid metabolism. Specifically, GLSO decreased the levels of metabolites such as lysophosphatidylcholine (LPC), glycerophosphatidylcholine (GPC), and sphinganine 1-phosphate (SA1P), while increasing the levels of phosphatidylglycerol (PG) and digalactosylceramide (DGC). Gut microbiomics data indicated that GLSO effectively regulated the composition of the gut microbiota in rats with acute liver injury. Specifically, it increased the abundance of Firmicutes and decreased the abundance of Proteobacteria. Mantel test correlation analysis revealed a close relationship between gut microbial Burkholderiales and lipid metabolites in GLSO-mediated prevention of acute liver injury. GLSO exerts its preventive effects on acute liver injury by remodeling the gut microbiota and regulating lipid metabolism. These findings provide novel insights and potential directions for the development of new drugs targeting acute liver injury.

A simple, fast, sample-saving, and sensitive liquid chromatography-tandem mass spectrometry method was established with a linear range adjusted by in-source collision-induced dissociation. Notably, this could simultaneously determine busulfan, fludarabine, phenytoin, and posaconazole in plasma from children, each having unique physical and chemical properties. The procedure necessitated only 20 μL of plasma and involved a simple protein precipitation process. Chromatographic separation was accomplished on a reversed-phase column (C18, 50 × 2.1 mm, 2.6 μm) through gradient elution utilizing water (containing 0.1 % formic acid and 2 mM ammonium acetate) and acetonitrile (containing 0.1 % formic acid) as the mobile phase. An injection volume of 2 μL was utilized, with a total run time of 3.6 min. Mass spectrum acquisition was performed on a Triple Quad™ 4500MD tandem mass spectrometer with an electrospray ionization source in positive mode. Moreover, in-source collision-induced dissociation was used to adjust the linear range of phenytoin due to its excessive response. The calibration curves ranged from 20 to 2560 ng/mL for busulfan, 10-1280 ng/mL for fludarabine, 0.4-51.2 μg/mL for phenytoin, and 0.1-12.8 μg/mL for posaconazole, with mean r greater than 0.997. In addition, the method underwent rigorous validation following the European Medicines Agency guidelines, demonstrating exceptional accuracy (90.5 %-106.7 %) and precision (2.0 %-13.0 %). Furthermore, its applicability to atypical matrices, including hemolytic and hyperlipidemic plasma, was thoroughly assessed. As such, this approach was effectively utilized for the therapeutic drug monitoring of busulfan, fludarabine, phenytoin, and posaconazole for children undergoing hematopoietic stem cell transplantation.

Etomidate and its structural analogues, which have anesthetic effects, are classified as controlled psychotropic drugs. Electronic cigarettes (e-cigarettes) have become more and more popular. With the increase of adding etomidate and its analogues to electronic liquids (e-liquids), there is a trend of abuse, which is a tough problem urgently need to be solved. This seriously affects the health and security of the public and the development of society. A simple, rapid and effective screening method is very crucial for their identification. In this study, we applied a newly developed method, probe electrospray ionization quadrupole time-of-flight mass spectrometry (PESI-QTOF-MS) with DPiMS QT ion source to analyze etomidate and its analogues in e-liquids. It allowed identification in 0.3 min with lower sample usage. Isomers can be distinguished by ion abundance ratios at collision energy (CE) 15 eV, which provided possibility for distinguishing more isomers by in-situ mass spectrometry. Limit of detection (LOD) and limit of quantitation (LOQ) of four substances were 20 ng/mL and 50 ng/mL, respectively. Good linear relationships were obtained in the concentration range of 50-5000 ng/mL with little matrix effect. The accuracy, precision, dilution effect and carryover of the method were also validated. Positive specimens (n = 38) were analyzed by both PESI-QTOF-MS and gas chromatography-mass spectrometry (GC-MS). There were five impurities including nicotine, cooling agent and flavorings were investigated by PESI-QTOF-MS, which provided the possibility for tracing the origin of illegal e-liquids. This study will help solve the backlog of cases and improve work efficiency effectively by reducing analysis time. Furthermore, it meets the need of addressing current situation of drug control and can assist forensic laboratories in investigating cases. It also demonstrates the application prospects of rapid screening in new drugs.

Agastache rugosa (AR), a traditional edible and medicinal herb, is often used for treating gastrointestinal (GI) motility disorder. But little effort has been done on its gastrointestinal motility modulation (GMM) efficacy-related components and quality control of AR. In this study, a novel strategy was proposed to find GMM efficacy-related chemical markers for the quality control of AR. Firstly, network pharmacology and serum pharmacochemistry were applied to predict potential GMM efficacy-related marker components. Secondly, the GMM efficacy-related marker components were verified through literature matching, target isolation/identification and activity evaluation. Lastly, a quantitative analysis of multiple components by a single marker (QAMS)-based method for simultaneous quantification of marker components was established and validated by HPLC-DAD. The results showed that nine components in AR were screened as potential GMM related components, five of which (rosmarinic acid, tilianin, apigenin, acacetin, and cirsimaritin) were matched by literatures, and four (acacetin-7-O-(6''-O-malonyl)-β-D-glucopyranoside, agastachoside, acacetin-7-O-(2''-O-acetyl-6''-O-malonyl)-β-D-glucopyranoside, and isoagastachoside) were chemically identified and newly evaluated on zebrafish model. The nine components were used as marker compounds to develop an effective QAMS-based method for the quantitative evaluation of 26 batches of commercial AR samples.

This study aimed to determine the chromatographic retention and dissociation/protonation constant (pK) values of lapatinib and tamoxifen, key drugs used in metastatic breast cancer treatment, at 37°C using both conventional and green high-performance liquid chromatography (HPLC) methods. Qualitative analysis was conducted on an XTerra C18 column (250 ×4.6 mm I.D., 5 μm particle size) at a flow rate of 1 mL/min. Hydroorganic mixtures with 45 %, 50 %, 55 %, and 60 % (v/v) organic modifiers were used to evaluate the retention times of the compounds. The compatibility of pK values pKass of the compounds in water-organic solvent mixtures obtained from these studies, which were carried out without any significant change in liquid chromatography performance, with the values obtained by the conventional method is remarkable. The pKass values determined in this study were correlated with the macroscopic parameters of acetonitrile, methanol, ethanol and the pK (pKaww)values of lapatinib and tamoxifen in water were calculated. The pKaww values calculated from these studies are compatible with each other and with the literature values. The environmental impact of the study, which was carried out using the green method and the conventional RPLC method, was evaluated using the Green Solvent Selection Tool (GSST), Green Analytical Procedures Index (GAPI), and Analytical Greenness Metric Approach (AGREE).

Near-infrared hyperspectral imaging (NIR-HSI) integrated with expert systems can support the monitoring of active pharmaceutical ingredients (APIs) and provide effective quality control of tablet formulations. However, existing quality control methods usually test a limited number of variability sources affecting the final product. This study examines the potential of NIR-HSI (in the spectral range of 935.61-1720.2 nm) as an advanced and high-throughput detector to identify different manufacturing factors and their fluctuations that impact tablet properties. These are, for instance, particle sizes of powdered excipients, their mixing, compression force used to form a tablet, origin of ingredients, storage conditions, and concentration of API. During the study, the novel expert system approach was developed to support NIR-HSI, enabling the detection of subtle, diverse substandard anomalies in tablets. The system combines (i) hyperspectrograms, which characterize and simplify tablet spatial heterogeneity through principal component analysis scores distribution, and (ii) a one-class classifier (OCC), trained exclusively on target class samples, without the need for substandard tablets. The system was trained to recognize known sources of variation and validated using tablets with cellulose, magnesium stearate, and ascorbic acid as API. It outperformed the alternative approach based on averaged spectra, achieving 100.00 % sensitivity and 98.77 % specificity.