Liquid chromatography (LC) has become indispensable for characterizing nasal and inhalation drug products, yet a critical gap persists in integrating chromatographic data with particle size metrics and in vitro performance outcomes to predict in vivo behavior. This review highlights recent advances in LC strategies from reversed-phase high-performance liquid chromatography to ultrahigh-performance liquid chromatography-tandem mass spectrometry; across three interconnected domains: formulation physicochemical characterization, aerodynamic particle size distribution determination, and comprehensive in vitro performance testing. We critically evaluated how LC-based quantification enables simultaneous active pharmaceutical ingredient and impurity profiling, dissolution kinetics assessment, and regional deposition mapping, with method validation data demonstrating linearity spanning three to four orders of magnitude and limits of detection as low as 5 pg/mL. Notably, we highlighted the mechanistic discrimination of erosion-vs. diffusion-controlled release enabled by simultaneous active pharmaceutical ingredient-polymer dissolution profiling and established quantitative correlations between particle size and systemic bioavailability. The review identified persistent challenges in biorelevant dissolution standardization and device-formulation interaction modeling while proposing integrated frameworks for bioequivalence prediction. This comprehensive perspective positions LC not merely as an analytical tool but as the central bridge connecting formulation properties, aerosol performance, and therapeutic outcomes, offering actionable insights for regulatory evaluation in respiratory drug delivery.

Cyclophosphamide (CP) is a common alkylating anticancer drug. Artemisinin (ART), an antimalarial agent metabolized by hepatic CYP450s, exhibits promising antitumor activity. This study established a rapid and accurate LC-MS/MS method for the quantitative analysis of CP and its metabolite in mouse plasma, as well as to apply this method in assessing how ART influences the pharmacokinetics of CP. Given the instability of 4-OH-CP, 4-keto-CP was selected as a surrogate metabolite for detection. The effect of ART on the mRNA expression and activity of CYP450 enzymes were assessed by RT-qPCR and substrate cocktail assay. The results indicated that CP and 4-keto-CP were linear in the range of 1-2000 and 2-2000 ng/mL, respectively. The accuracy, precision, extraction recovery, stability, and matrix effect of CP and 4-keto-CP are complied with the Bioanalytical Method Validation Guidelines. ART significantly reduced the AUC0-t of CP by 26.6%, while increasing CL/F by 1.35-fold. Concurrently, the AUC0-t and Cmax of 4-keto-CP increased by 1.42- and 1.45-fold, respectively. Furthermore, ART can markedly upregulate the mRNA expression and activity of CAR/CYP2B6. The results showed that pretreatment with ART could induce CP metabolism to its active metabolite. This study provides implications for the rational use of the ART-CP combination in clinical practice.

Cystic fibrosis, a genetic disorder caused by mutations in the CFTR gene, is commonly treated using combination therapy with IVA and LUMA. Accurate quantification of these drugs in human plasma is essential for therapeutic monitoring; however, conventional analytical methods often lack sufficient sensitivity and robustness. In this study, a QbD-based RP-UPLC method was developed and validated for the simultaneous estimation of IVA and LUMA in human plasma. The primary objective was to achieve efficient separation of analytes from plasma interferences with reduced run time and consistent analytical performance. Chromatographic separation was carried out using a Waters Acquity UPLC system equipped with a CSH C18 column (100 mm × 2.1 mm, 1.8 μm). Method optimization was performed using a Central Composite Design model. The mobile phase is 0.01 N ammonium acetate and acetonitrile (60:40, v/v) at a flow rate of 0.3 mL/min, with the column maintained at 30°C. EMT was used as the internal standard, and detection was conducted at 260 nm. The retention times were 1.45, 1.77, and 1.99 min for EMT, IVA, and LUMA, respectively. The method is reliable, rapid and selective, exhibiting excellent linearity, precision, and accuracy, complying with USFDA guidelines.

Colorectal cancer (CRC) arises via the stepwise adenoma-carcinoma sequence (ACS). Gut microbial dysbiosis and host metabolic reprogramming jointly correlate with CRC onset and advancement, yet their stage-specific crosstalk across ACS remains largely unclear. Limited multi-omics research on microbial-metabolic interactions throughout ACS hinders the development of early diagnostic biomarkers and preventive strategies. Here, we combined untargeted mucosal metabolomics and fecal shotgun metagenomic sequencing in 36 participants, covering healthy controls, ACS, and CRC patients. We systematically analyzed microbial composition, functions, differential metabolites, and enriched pathways and integrated multi-omics data to screen stage-specific signatures. Distinct gut microbial profiles and progressive functional shifts toward pathogenicity and abnormal carbohydrate metabolism were observed along ACS. Mucosal metabolism was continuously disrupted, with prominent alterations in taurine-hypotaurine, sphingolipid, and bile acid pathways. Core differential metabolites showed excellent diagnostic performance. Microbe-metabolite interactions were progressively enhanced to form a concerted pro-tumor axis. This study characterizes unique ACS-stage microbial-metabolic features. Dysregulated metabolic pathways and key microbe-metabolite crosstalk are closely associated with CRC progression, offering novel non-invasive biomarkers and premalignant intervention targets.

A stability-indicating reverse-phase high-performance liquid chromatographic (RP-HPLC) method was developed and validated for quantitative estimation of satranidazole in bulk drug and tablet dosage form, followed by LC-MS characterization of stress-induced degradation products. Chromatographic separation was achieved on a HiQ Sil C18 column (250 × 4.6 mm, 5 μm) using methanol:0.1% formic acid in water (60:40, v/v) as mobile phase at a flow rate of 1.0 mL/min with UV detection at 317 nm. The method exhibited satisfactory linearity over 5-30 μg/mL with a correlation coefficient of 0.999. Stress-induced degradation studies performed under acidic, alkaline, oxidative, thermal, and photolytic conditions demonstrated significant degradation under alkaline and photolytic stress. The developed method successfully resolved satranidazole from its degradation products. LC-MS analysis enabled tentative characterization of major degradants and facilitated the proposal of probable degradation pathways. The developed method is suitable for routine stability assessment and pharmaceutical quality control of satranidazole formulations.

Dazhu Hongjingtian (DZ), a traditional Tibetan medicine used for altitude sickness and blood stasis syndrome, currently lacks comprehensive pharmacological and quality control data. This study evaluated its antihypoxic effects in mice and established an HPLC-MS/MS method for quantifying 12 bioactive constituents. Acute hypoxic injury was induced by 12-h normobaric hypoxia (10% O2), and DZ water extract (DZE) was assessed via ELISA for oxidative stress, inflammation, and energy metabolism markers in brain, lung, heart, and liver. DZE dose-dependently attenuated oxidative stress (reduced H2O2 and MDA; elevated SOD, T-AOC, and GSH-Px), inhibited inflammation (reduced TNF-α, IL-1β, and IL-6), and improved energy metabolism (enhanced Na+-K+-ATPase and ATP; reduced LDH and lactate). The HPLC-MS/MS method showed good linearity (r ≥ 0.9957), precision (RSD < 5%), and recovery (94.11%-102.46%). Gallic acid derivatives dominated the constituents (19.77 mg/g), followed by salidroside (12.15 mg/g) and flavonoids (6.62 mg/g). These findings demonstrate that DZE exerts potent antihypoxic effects through synergistic action of its macro- and micro-components, providing a mechanistic and analytical foundation for its use in the prevention and treatment of hypoxia-related diseases, particularly acute mountain sickness.

Pharmaceutical and cosmetic preservatives play a critical role in inhibiting microbial contamination, preventing chemical degradation, and maintaining product efficacy and safety throughout the shelf life. Given their functional importance, comparable to that of active pharmaceutical ingredients, it is essential to monitor their quality using advanced analytical techniques. Among the most commonly employed seven varieties of preservatives in industry are 2,4-dihydroxybenzoic acid, 4-hydroxybenzoic acid, 3,4-dihydroxybenzoic acid, benzyl alcohol, benzaldehyde, phenol, sodium benzoate, methylparaben, and propylparaben, either individually or in combination. The present study focuses on the development and validation of a stability-indicating, reverse-phase high-performance liquid chromatography method for simultaneous quantification of these seven preservatives and their impurities, benzaldehyde and phenol, a total of nine components. The method demonstrates high selectivity, sensitivity, accuracy, and precision, and meets the validation criteria outlined in International Council for Harmonization (ICH) guidelines. Optimal chromatographic resolution was achieved using a Phenomenex Luna C18 column, dual-wavelength UV detection at 254 and 230 nm, and a gradient mobile phase consisting of 0.1% orthophosphoric acid and acetonitrile. The method was established within a range of 1.5-45.0μg/mL concentration for all components. The validated method is suitable for routine quality control testing across various pharmaceutical and cosmetic formulations.

For many years, it is known as Nitrosamines are responsible for carcinogenicity in human. These nitroso-impurities were found detected in plastics, food items, cigarette, insect killer, water and alcoholic beverages. In 2018 EMA and USFDA claimed the presence of N-nitrosodimethylamine in valsartan used for the treatment of hypertension. Consequently, to assess the adverse effects of nitrosamine generation during storage, in the course of production, or through contaminated supply chains, regulators have issued many guidelines. Hence, there is a crucial need for accurate evaluation technique to measure nitroso-impurities in pharmaceutical products. According to the Carcinogenic Potency Categorization Approach, the allowable intake is 400 ng/day, which translates to an allowable limit of 16 ppm for a 25 mg daily dose. A study was then performed at 1.5 ppm relative to sample concentration, which is less than 10% of this limit. The main aim of this development to optimize and prove suitability of a new liquid chromatography-tandem mass spectrometry method for quantitatively analyzing 3-amino-N-nitrosopiperidine (NTPA) in Alogliptin Benzoate (AGP), achieving detectable response of 0.03 ppm and quantifiable response value of 0.1 ppm relative to sample concentration. Current method was found to be linear with the coefficient of regression of 0.9979. Also, spiking study was performed by the calculating percentage spiked NTPA in the drug, which ranged from 96.67% to 100.14%. The results confirmed that the methodology was reliable, precise, robust and reproducible to quantify NTPA at 1.5 ppm in samples of 2.75 mg/mL concentration.

Benzene (BENZ) is classified as a Class 1 residual solvent according to ICH Q3C guidelines due to its established classification as a Group 1 human carcinogen. During the chemical production of Cetirizine Dihydrochloride (CTZ) API, Cetirizine Dihydrochloride tablet (CTZT), Levocetirizine Dihydrochloride (LCTZ) API, and Levocetirizine Dihydrochloride tablet (LCTZT), BENZ can appear as a residual process impurity with carcinogenic risk; development of a highly sensitive quantification method is a critical requirement for pharmaceutical quality control. This study focused on developing and validating a method for detecting trace-level BENZ in CTZ and LCTZ drug substance and drug product. The method demonstrated exceptional sensitivity, with a least detectable concentration of 0.04 ppm and a quantifiable concentration of 0.12 ppm, significantly lower than the ICH-mandated safety limit of 2 ppm. Linearity and accuracy studies yielded an outstanding percentage of samples spiked BEN in the drug substance and drug product of CTZ and LCTZ and found within acceptance limit, approving the method's validity in presence of the drug atmosphere. Conventional headspace GC-FID/GC-MS are established techniques for benzene analysis; the proposed HPLC method offers a simpler, cost-effective, and validated method, making it well suited for routine quality control laboratories where GC facilities may not be readily available.

Thiopurine immunosuppressive drugs are indicated in children with acute lymphoblastic leukemia and in both children and adults with chronic inflammatory diseases. Therapeutic drug monitoring (TDM) of its DNA-incorporated metabolites 6-thioguanine nucleotides (6TGN) and 6-methylmercaptopurine nucleotides (6MMPN) is of high interest to optimize efficacy and prevent toxicity. The objective of this study was to develop and validate a sensitive and simple LC-MS/MS method for the simultaneous quantification of 6TGN and 6MMPN in whole blood for TDM. Following red blood cell count and whole blood extraction with dithiothreitol plus acidic hydrolysis at 100°C, quantification was performed using an LC-MS/MS in positive ionization mode. Calibration curves were linear over the range of 20-1000 ng/mL for 6TGN and 20-20,000 ng/mL for 6MMPN, with correlation coefficients above 0.99 for all analytes. Intra- and inter-day precisions were below 9.45%. Extraction recovery and matrix effects reached 78.9%-83.2% and 121% for 6TGN and 92.2%-95.2% and 112%-118% for 6MMPN, respectively. The method was applied to 749 clinical samples from patients with acute lymphoblastic leukemia or chronic inflammatory diseases. A sensitive and simple LC-MS/MS method was validated for 6TGN and 6MMPN in whole blood and was successfully applied to clinical samples for TDM.

Stable isotope-resolved metabolomics (SIRM) has emerged as a pivotal methodology for dissecting mitochondrial metabolic reprogramming and its connection to therapeutic targets. By combining isotopically labeled substrates with metabolic flux analysis (MFA), SIRM enables dynamic, quantitative tracking of carbon flux through mitochondrial pathways. This review focuses on three disease contexts where SIRM has provided transformative insights: cancer, neurodegenerative disorders (Alzheimer's and Parkinson's diseases), and metabolic syndrome (type 2 diabetes and non-alcoholic fatty liver disease). Recent applications have delineated reprogramming signatures, identified metabolic dependencies, and elucidated drug mechanisms. SIRM also facilitates therapeutic monitoring and resistance assessment, offering quantitative biomarkers for patient stratification. We summarize recent advances, technical challenges, AI-powered innovations, and future directions, providing a foundation for optimizing metabolism-targeted therapies.

This study aimed to elucidate the therapeutic effect and mechanism of Zhuangdu Quhan Mixture (ZDQHM) in ankylosing spondylitis (AS). An AS mouse model was established in mice using β-glucan. Therapeutic efficacy was assessed through arthritis scores, histopathology, serum cytokine measurement by ELISA, and bone metabolism-related protein analysis via Western blot. Active compounds were identified by UHPLC-MS, with targets predicted using network pharmacology and validated by molecular docking and molecular dynamics simulations. ZDQHM significantly ameliorated spinal inflammation and histopathological damage, reduced serum IL-6 and TNF-α levels, and modulated bone metabolism proteins. Network pharmacology identified 45 intersecting targets between ZDQHM compounds and AS, predominantly enriched in IL-17, Toll-like receptor, and NOD-like receptor pathways. Molecular docking and dynamics demonstrated binding of key compounds to IL-17A. In vivo validation revealed that ZDQHM suppressed IL-17A, Act1, and IL-17RA expression, and recombinant IL-17A partially reversed its therapeutic effects. ZDQHM alleviates inflammation and abnormal bone metabolism in AS mice, potentially through inhibition of the IL-17 signaling pathway. Beyond confirming the established role of IL-17 in AS, this study provides an integrated pharmacological framework explaining how ZDQHM exerts its effects via regulation of the IL-17A/IL-17RA/Act1 axis, offering mechanistic insights and experimental support for TCM in AS therapy.

Betel leaf (Piper betle L.) has been widely used in traditional medicine for treating pain, inflammation, and microbial infections due to its rich phytochemical content. However, the molecular mechanisms underlying its analgesic and anti-inflammatory effects remain incompletely understood. This study aimed to analyze the phytochemical composition of betel leaf oil using GC-MS and to explore its therapeutic mechanisms through network pharmacology targeting genes involved in pain and inflammation pathways. Betel leaf essential oil was extracted and analyzed with GC-MS to identify bioactive metabolites. The identified compounds were further examined using network pharmacology to predict target genes and develop compound-protein interaction networks. Gene ontology enrichment, DisGeNET disease enrichment, and gene-disease association analyses were conducted to investigate biological pathways and disease relevance. The GC-MS analysis revealed bioactive compounds including estragole, oleic acid, chavicol acetate, and eugenol, interacting strongly with genes such as SCN9A, SCN10A, TRPV1, ICAM1, STAT3, TNF, and BDNF involved in pain and inflammatory responses. The findings suggest that the bioactive components of betel leaf oil may possess analgesic and anti-inflammatory properties, indicating its potential as a source of therapeutic agents. Molecular docking further demonstrated favorable binding of eugenol and oleic acid with TNF-α and TRPV1, supporting their potential anti-inflammatory and analgesic activities. These integrated findings suggest that the bioactive constituents of betel leaf oil possess potential analgesic and anti-inflammatory activities through multi-target interactions, although further experimental validation is required.

The theory of medicinal properties of traditional Chinese medicine is the core guideline for syndrome differentiation and medication. Herba Siegesbeckiae (HS) is cold in property, and its medicinal property changes from cold to warm after processing. Based on metabolomics technology, this study investigates the regulatory effects of processed HS (pro- HS) and its separated fractions on the neuro-endocrine-metabolic network in cold syndrome rats, aiming to clarify the characteristics associated with medicinal properties. Chemical separation techniques were employed to isolate the main chemical components of pro-HS. A cold syndrome rat model was established via ice water stimulation. Differential expression metabolites (DEMs) and key metabolic pathways were screened by metabolomics, and combined ELISA technology to detect neuro-endocrine-metabolic-related indicators. A total of 48 DEMs were identified, involving 11 core metabolic pathways. Pro-HS and its diterpenoid fraction exerted regulatory effects on the abnormal neurotransmitters, thyroid hormones, and energy metabolism enzyme activities in cold syndrome rats. The pro-HS and its separated fractions exert targeted regulatory effects on metabolic disorders in cold syndrome rats. The mechanism is closely associated with the regulation of the neuro-endocrine-energy metabolism network and related metabolic pathways.

This study optimized the freeze-drying process of Scorpio, compared its chemical and pharmacodynamic equivalence with traditional salt-processed Scorpio in treating CIA model rats, established an equivalent conversion relationship, and evaluated acute toxicity. Single-factor experiments and orthogonal tests were conducted with prefreezing time, drying time, and temperature as factors and water-soluble protein content, ethanol-soluble extract content, and freeze-drying rate as indices. The analytic hierarchy process-criteria importance through intercriteria correlation (AHP-CRITIC) mixed weighting method was used for comprehensive scoring to determine the optimal process. Chemical equivalence was calculated using four amino acids and water-soluble protein content. Pharmacodynamic equivalence was evaluated in a complete Freund's adjuvant-induced arthritis rat model using arthritis index, rheumatoid factor, and serum inflammatory cytokines (IL-6, TNF-α, and IL-1β). Acute toxicity was assessed by determining the LD5 0. Results showed that freeze-killing pretreatment was superior to scalding. The optimal process was prefreezing for 2 h, drying at 45°C for 16 h. Chemical equivalence indicated that 1 g of freeze-dried Scorpio was equivalent to 1.455 g of salt-processed Scorpio. Pharmacodynamic equivalence showed that 1 g of freeze-dried Scorpio was equivalent to 1.081 g of salt-processed Scorpio. The LD5 0 of freeze-dried Scorpio was 11.091 g/kg.