Seasonal variation and human health risk assessment of potentially toxic elements in pharmaceutical effluents around Ilorin metropolis, Nigeria.

Potentially toxic elements (PTEs) are widely released into the environment as a result of increased urban and industrial development in recent years. The bulk of PTEs are cancer-causing and harm human health by producing free radicals. As a result, it is crucial to monitor, evaluate, and limit the effects of the elements on human health. In this study, levels of PTEs (As, Cr, Cd, Ni, Co, and Pb) in pharmaceutical effluents discharged along the Asa River around the Ilorin metropolis and their seasonal variations were evaluated. Water samples were collected from eight different locations over a two-season period along the river and analyzed for PTEs using atomic absorption spectrophotometry and an inductively coupled plasma optical emission spectrometer. As, Cd, Pb, Cr, Ni, and Co had mean PTE values in the effluents (both seasons) of 0.0258, 0.0233, 0.00193, 0.0176, and 0.0164 mg/L, respectively, with As and Pb surpassing the WHO standard. Maximum temperature and pH were measured for the physicochemical parameters in the wet season, whereas electrical conductivity and total dissolved solids were seen in the dry season. The average values of the metals in the human risk assessment for carcinogenicity were As > Cd > Pb > Cr > Ni > Co, with As above the recommended threshold in several locations. However, all of the metal hazard indices were < 1, indicating that the waters were suitable for domestic purposes. Nonetheless, the relevant authorities should mandate that pharmaceutical effluents be treated before being released into bodies of water.

An FDA-Validated, Self-Cleaning Liquid Chromatography-Mass Spectrometry System for Determining Small-Molecule Drugs and Metabolites in Organoid/Organ-on-Chip Medium.

As organoids and organ-on-chip (OoC) systems move toward preclinical and clinical applications, there is an increased need for method validation. Using a liquid chromatography-mass spectrometry (LC-MS)-based approach, we developed a method for measuring small-molecule drugs and metabolites in the cell medium directly sampled from liver organoids/OoC systems. The LC-MS setup was coupled to an automatic filtration and filter flush system with online solid-phase extraction (SPE), allowing for robust and automated sample cleanup/analysis. For the matrix, rich in, e.g., protein, salts, and amino acids, no preinjection sample preparation steps (protein precipitation, SPE, etc.) were necessary. The approach was demonstrated with tolbutamide and its liver metabolite, 4-hydroxytolbutamide (4HT). The method was validated for analysis of cell media of human stem cell-derived liver organoids cultured in static conditions and on a microfluidic platform according to Food and Drug Administration (FDA) guidelines with regards to selectivity, matrix effects, accuracy, precision, etc. The system allows for hundreds of injections without replacing chromatography hardware. In summary, drug/metabolite analysis of organoids/OoCs can be performed robustly with minimal sample preparation.

Are pharmaceutical residues in crops a threat to human health?

The application of biosolids, manure, and slurry onto agricultural soils and the growing use of treated wastewater in agriculture result in the introduction of human and veterinary pharmaceuticals to the environment. Once in the soil environment, pharmaceuticals may be taken up by crops, resulting in consequent human exposure to pharmaceutical residues. The potential side effects of pharmaceuticals administered in human medicine are widely documented; however, far less is known regarding the risks that arise from incidental dietary exposure. The aim of this study was to evaluate human exposure to pharmaceutical residues in crops and assess the associated risk to health for a range of pharmaceuticals frequently detected in soils. Estimated concentrations of carbamazepine, oxytetracycline, sulfamethoxazole, trimethoprim, and tetracycline in soil were used in conjunction with plant uptake and crop consumption data to estimate daily exposures to each compound. Exposure concentrations were compared to Acceptable Daily Intakes (ADIs) to determine the level of risk. Generally, exposure concentrations were lower than ADIs. The exceptions were carbamazepine, and trimethoprim and sulfamethoxazole under conservative, worst-case scenarios, where a potential risk to human health was predicted. Future research therefore needs to prioritize investigation into the health effects following exposure to these compounds from consumption of contaminated crops.

Leveraging AI and Machine Learning in Six-Sigma Documentation for Pharmaceutical Quality Assurance.

The pharmaceutical industry must maintain stringent quality assurance standards to ensure product safety and regulatory compliance. A key component of the well-known Six Sigma methodology for process improvement and quality control is precise and comprehensive documentation. However, there are a number of significant issues with traditional documentation procedures, including as slowness, human error, and difficulties with regulatory standards. This review research looks at innovative ways to employ machine learning (ML) and artificial intelligence (AI) to enhance Six Sigma documentation processes in the pharmaceutical sector. AI and ML provide cutting-edge technologies that have the potential to drastically alter documentation processes by automating data entry, collection, and analysis. Natural language processing (NLP) and computer vision technologies have the potential to significantly reduce human error rates and increase the efficacy of documentation processes. By applying machine learning algorithms to support real-time data analysis, predictive analytics, and proactive quality management, pharmaceutical organizations may be able to identify potential quality issues early on and take proactive efforts to address them. Combining AI and ML improves documentation accuracy and reliability while also strengthening compliance with stringent regulatory criteria. The primary barriers and limitations to the current state of Six Sigma documentation in the pharmaceutical industry are identified in this study. It examines the fundamentals of AI and ML with an emphasis on their specific applications in quality assurance and potential benefits for Six Sigma processes. The report includes extensive case studies that highlight notable developments and explain how AI/ML enhanced documentation is used in the real world.

Occurrence of pharmaceuticals in Latin America: case study on hazard assessment and prioritization in Costa Rica.

Pharmaceuticals are considered as contaminants of emerging concern, and their occurrence in diverse environmental matrices has been described during the last 25 years. Nonetheless, pharmaceutical occurrence has not been evenly described worldwide, and reports from some geographical areas such as most parts of Latin America are scarce. This work aims to address the situation of water pollution due to pharmaceuticals in Latin America by means of two main goals: i. First, reviewing the monitoring studies performed in Latin America on this topic (period 2009-2024), which were conducted in Brazil, Mexico, Colombia, Ecuador, Peru and Argentina, to highlight the most frequently detected compounds from each therapeutic group in the region. ii. Second, analyzing the case of Costa Rica through the hazard assessment and prioritization of pharmaceuticals based on the monitoring performed in this country (years 2011; 2018-2019). The monitoring in Costa Rica comprised a total of 163 sampling points: wastewater treatment plants (WWTPs) (14 urban WWTPs plus two landfill WWTPs; total samples n = 44 influents and n = 34 effluents), nine hospital effluents (n = 32), wastewater from livestock farms (six swine farms and seven dairy farms; n = 23 influents and n = 37 effluents), 64 continental surface water sampling points (n = 137), and 61 coastal seawater sampling points (n = 61). Risk assessment of detected concentrations by the hazard quotient (HQ) approach (period 2018-2019) revealed a total of 25 medium or high-hazard compounds (out of 37 detected compounds). The prioritization approach (which included the Frequency of Appearance (FoA), the Frequency of PNEC exceedance (FoE), and the Extent of predicted no-effect concentration (PNEC) exceedance (EoE)), showed a critical list of nine pharmaceuticals: caffeine, diphenhydramine, acetaminophen, lovastatin, gemfibrozil, ciprofloxacin, ibuprofen, doxycycline and norfloxacin. These compounds should be taken into account as a first concern during the implementation of environmental policies related to pharmaceutical products in the region.

Multimodal Image Fusion Workflow Incorporating MALDI Imaging Mass Spectrometry and Microscopy for the Study of Small Pharmaceutical Compounds.

Multimodal imaging analyses of dosed tissue samples can provide more comprehensive insights into the effects of a therapeutically active compound on a target tissue compared to single-modal imaging. For example, simultaneous spatial mapping of pharmaceutical compounds and endogenous macromolecule receptors is difficult to achieve in a single imaging experiment. Herein, we present a multimodal workflow combining imaging mass spectrometry with immunohistochemistry (IHC) fluorescence imaging and brightfield microscopy imaging. Imaging mass spectrometry enables direct mapping of pharmaceutical compounds and metabolites, IHC fluorescence imaging can visualize large proteins, and brightfield microscopy imaging provides tissue morphology information. Single-cell resolution images are generally difficult to acquire using imaging mass spectrometry but are readily acquired with IHC fluorescence and brightfield microscopy imaging. Spatial sharpening of mass spectrometry images would thus allow for higher fidelity coregistration with other higher-resolution microscopy images. Imaging mass spectrometry spatial resolution can be predicted to a finer value via a computational image fusion workflow, which models the relationship between the intensity values in the mass spectrometry image and the features of a high-spatial resolution microscopy image. As a proof of concept, our multimodal workflow was applied to brain tissue extracted from a Sprague-Dawley rat dosed with a kratom alkaloid, corynantheidine. Four candidate mathematical models, including linear regression, partial least-squares regression, random forest regression, and two-dimensional convolutional neural network (2-D CNN), were tested. The random forest and 2-D CNN models most accurately predicted the intensity values at each pixel as well as the overall patterns of the mass spectrometry images, while also providing the best spatial resolution enhancements. Herein, image fusion enabled predicted mass spectrometry images of corynantheidine, GABA, and glutamine to approximately 2.5 µm spatial resolutions, a significant improvement compared to the original images acquired at 25 µm spatial resolution. The predicted mass spectrometry images were then coregistered with an H&E image and IHC fluorescence image of the µ-opioid receptor to assess colocalization of corynantheidine with brain cells. Our study also provides insights into the different evaluation parameters to consider when utilizing image fusion for biological applications.

Bioconcentration of pharmaceuticals by aquatic flora in an Australian river system.

Pharmaceuticals are emerging contaminants in the environment and are a ubiquitous presence in rivers downstream of wastewater treatment plant outfalls. Questions remain about the persistence of pharmaceuticals in rivers, and the uptake and bioconcentration of pharmaceuticals by aquatic plants. Our study took place in the Yarrowee/Leigh/Barwon River system in southeastern Australia. We quantified the concentrations of five pharmaceuticals (carbamazepine, primidone, propranolol, tramadol, and venlafaxine) in surface water at five sites along a 144-km stretch of river, downstream of the presumed primary point source (a wastewater treatment plant outfall). We quantified pharmaceuticals in the leaves of two aquatic plant species (Phragmites australis and Vallisneria australis) sampled at each site, and calculated bioconcentration factors. All five pharmaceuticals were detected in surface waters, and the highest detected concentration exceeded 500 ng.L-1 (tramadol). Four of the pharmaceuticals (all except tramadol) were detected and quantified at all sites, including the furthest site from the outfall (144 km). Carbamazepine showed less attenuation with distance from the outfall than the other pharmaceuticals. Carbamazepine and venlafaxine were quantified in the leaves of both aquatic plant species (range: 10-31 ng.g-1), and there was evidence that bioconcentration factors increased with decreasing surface water concentrations. The study demonstrates the potential long-distance persistence of pharmaceuticals in river systems, and the bioconcentration of pharmaceuticals by aquatic plants in natural ecosystems. These phenomena deserve greater attention as aquatic plants are a potential point of transfer of pharmaceuticals from aquatic ecosystems to terrestrial food webs.

The behavior of pharmaceutically active compounds and contrast agents during wastewater treatment - Combining sampling strategies and analytical techniques: A critical review.

Increasing consumption of pharmaceuticals and the respective consequences for the aquatic environment have been the focus of many studies over the last thirty years. Various aspects in this field were investigated, considering diverse pharmaceutical groups and employing a wide range of research methodologies. Various questions from the perspectives of different research areas were devised and answered, resulting in a large mix of individual findings and conclusions. Collectively, the results of the studies offer a comprehensive overview. The large variety of methods and strategies, however, demands close attention when comparing and combining information from heterogeneous projects. This review critically examines the application of diverse sampling techniques as well as analytical methods in investigations concerning the behavior of pharmaceutically active compounds (PhACs) and contrast agents (CAs) in wastewater treatment plants (WWTPs). The combination of sampling and analysis is discussed with regard to its suitability for specific scientific problems. Different research focuses need different methods and answer different questions. An overview of studies dealing with the fate and degradation of PhACs and CAs in WWTPs is presented, discussing their strategic approaches and findings. This review includes surveys of anticancer drugs, antibiotics, analgesics and anti-inflammatory drugs, antidiabetics, beta blockers, hormonal contraceptives, lipid lowering agents, antidepressants as well as contrast agents for X-ray and magnetic resonance imaging.

A Novel Apparatus for the Fully Automated Extraction and Online Liquid Chromatographic Analysis of Solid Environmental Samples: Application to the Pressurized Hot Water Extraction of Pharmaceuticals in Soil.

A new self-assembled apparatus for the extraction of solid samples was designed and implemented to perform a recirculated pressurized hot water extraction (R-PHWE) directly coupled to liquid chromatography-tandem mass spectrometry. To investigate the potential of this new extraction apparatus, 34 target pharmaceutical compounds were analyzed in loam, silt-loam, and silty-clay-loam soils. The target analytes were characterized by heterogeneous physicochemical properties (e.g., -1.60 ≤ log D ≤ 5.91 at pH = 7.2, i.e., at the mean pH values of the three soils). Design of experiments (DoE) was used to identify the best extraction conditions for the target analytes by studying temperature, pressure, and number of extraction cycles. The results of DoE optimization pointed out the significant influence of the number of cycles on recovery. The application of DoE set point to the three reference soils provided recoveries ≥60% for 21-25 out the 34 target analytes, depending on soil. Good recovery precision (<25%) and moderate suppressive matrix effect (≤40%) were found for most target analytes, regardless of the soil considered. The optimized R-PHWE procedure evidenced statistically higher recoveries for 16 out of 34 target analytes when compared to conventional off-line dynamic PHWE.

[Establishment of collection methods and laboratory testing methods for active pharmaceutical ingredient in the workplace air].

Objective: To establish collection methods and laboratory testing methods for qualitative and quantitative analysis of 9 typical active pharmaceutical ingredient in the workplace air. Methods: In December 2021, a mixed solution of nine analytes was prepared and then dispersed in aerosol state to simulate sampling. Glass fiber filter membrane was selected as air collector and collected active pharmaceutical ingredient in the air at a rate of 2.0 L/min for 15 minutes. Then, the obtained filter membrane samples were eluted with 25%ACN/75%MeOH. Finally, the eluent was qualitatively and quantitatively analyzed with liquid chromatography-triple quadrupole mass spectrometer. Results: This method could effectively collect active pharmaceutical ingredient in the air, with an average sampling efficiency of more than 98.5%. The linear correlation coefficient r was greater than 0.9990. The lower limit of quantification for each analyte ranged from 0.6~500.0 ng/ml, and the average recovery rate ranged from 97.6%~102.5%. Conclusion: This method could simultaneously collect 9 active pharmaceutical ingredient in the workplace air, and could provide accurate qualitative and quantitative analysis in subsequent laboratory tests.

Development of an eco-friendly fluorescent probe for mefenamic acid sensing in pharmaceuticals and biofluids.

Mefenamic acid, renowned for its analgesic properties, stands as a reliable choice for alleviating mild to moderate pain. However, its versatility extends beyond pain relief, with ongoing research unveiling its promising therapeutic potential across diverse domains. A straightforward, environmentally friendly, and sensitive spectrofluorometric technique has been developed for the precise quantification of the analgesic medication, mefenamic acid. This method relies on the immediate reduction of fluorescence emitted by a probe upon interaction with varying concentrations of the drug. The fluorescent probe utilized, N-phenyl-1-naphthylamine (NPNA), was synthesized in a single step, and the fluorescence intensities were measured at 480 nm using synchronous fluorescence spectroscopy with a wavelength difference of 200 nm. Temperature variations and lifetime studies indicated that the quenching process was static. The calibration curve exhibited linearity within the concentration range of 0.50-9.00 µg/mL, with a detection limit of 60.00 ng/mL. Various experimental parameters affecting the quenching process were meticulously examined and optimized. The proposed technique was successfully applied to determine mefenamic acid in pharmaceutical formulations, plasma, and urine, yielding excellent recoveries ranging from 98% to 100.5%. The greenness of the developed method was evaluated using three metrics: the Analytical Eco-scale, AGREE, and the Green Analytical Procedure Index.

Occurrence and risks of pharmaceuticals, personal care products, and endocrine-disrupting compounds in Chinese surface waters.

The continuous and rapid increase of chemical pollution in surface waters has become a pressing and widely recognized global concern. As emerging contaminants (ECs) in surface waters, pharmaceutical and personal care products (PPCPs), and endocrine-disrupting compounds (EDCs) have attracted considerable attention due to their wide occurrence and potential threat to human health. Therefore, a comprehensive understanding of the occurrence and risks of ECs in Chinese surface waters is urgently required. This study summarizes and assesses the environmental occurrence concentrations and ecological risks of 42 pharmaceuticals, 15 personal care products (PCPs), and 20 EDCs frequently detected in Chinese surface waters. The ECs were primarily detected in China's densely populated and highly industrialized regions. Most detected PPCPs and EDCs had concentrations between ng/L to µg/L, whereas norfloxacin, caffeine, and erythromycin had relatively high contamination levels, even exceeding 2000 ng/L. Risk evaluation based on the risk quotient method revealed that 34 PPCPs and EDCs in Chinese surface waters did not pose a significant risk, whereas 4-nonylphenol, 4-tert-octylphenol, 17α-ethinyl estradiol, 17ß-estradiol, and triclocarban did. This review provides a comprehensive summary of the occurrence and associated hazards of typical PPCPs and EDCs in Chinese surface waters over the past decade, and will aid in the regulation and control of these ECs in Chinese surface waters.

Process analytical technology in Downstream-Processing of Drug Substances- A review.

Process Analytical Technology (PAT) has revolutionized pharmaceutical manufacturing by providing real-time monitoring and control capabilities throughout the production process. This review paper comprehensively examines the application of PAT methodologies specifically in the production of solid active pharmaceutical ingredients (APIs). Beginning with an overview of PAT principles and objectives, the paper explores the integration of advanced analytical techniques such as spectroscopy, imaging modalities and others into solid API substance production processes. Novel developments in in-line monitoring at academic level are also discussed. Emphasis is placed on the role of PAT in ensuring product quality, consistency, and compliance with regulatory requirements. Examples from existing literature illustrate the practical implementation of PAT in solid API substance production, including work-up, crystallization, filtration, and drying processes. The review addresses the quality and reliability of the measurement technologies, aspects of process implementation and handling, the integration of data treatment algorithms and current challenges. Overall, this review provides valuable insights into the transformative impact of PAT on enhancing pharmaceutical manufacturing processes for solid API substances.

Elimination of microplastics, PFAS, and PPCPs from biosolids via pyrolysis to produce biochar: Feasibility and techno-economic analysis.

Biosolids from municipal wastewater treatment contain many contaminants of emerging concern, including microplastics (MPs), per- and polyfluoroalkyl substances (PFAS), pharmaceuticals and chemicals from personal care products (PPCPs). Many of these contaminants have very slow biotic or abiotic degradation rates and have been shown to have human and ecological health impacts. Application of biosolids to agriculture, a common disposal method, can result in extended environmental contamination. An approach for eliminating the contaminants is pyrolysis, which can also generate biochar, enhancing carbon sequestration as a side-benefit. We pyrolyzed biosolid samples from an operating facility at various temperatures from 400 to 700 °C with a 2-hour residence time. We then evaluated contaminant removal, which in many cases was 100 %, with only a few residuals. No trace of PFAS was detectable even at 400 °C. Overall mass removal of PPCPs, including PFAS, was over 99.9 %. MP removal via pyrolysis ranged from 91 to 97 %. The biochar contains significant amounts of Fe and P, which make it a useful fertilizer amendment. The techno-economic analysis indicates that pyrolysis may generate significant cost savings, and revenue from the sale of biochar, sufficient to more than cover the investment and operating costs of the dryer and pyrolysis unit.

Machine learning models and performance dependency on 2D chemical descriptor space for retention time prediction of pharmaceuticals.

The predictive modeling of liquid chromatography methods can be an invaluable asset, potentially saving countless hours of labor while also reducing solvent consumption and waste. Tasks such as physicochemical screening and preliminary method screening systems where large amounts of chromatography data are collected from fast and routine operations are particularly well suited for both leveraging large datasets and benefiting from predictive models. Therefore, the generation of predictive models for retention time is an active area of development. However, for these predictive models to gain acceptance, researchers first must have confidence in model performance and the computational cost of building them should be minimal. In this study, a simple and cost-effective workflow for the development of machine learning models to predict retention time using only Molecular Operating Environment 2D descriptors as input for support vector regression is developed. Furthermore, we investigated the relative performance of models based on molecular descriptor space by utilizing uniform manifold approximation and projection and clustering with Gaussian mixture models to identify chemically distinct clusters. Results outlined herein demonstrate that local models trained on clusters in chemical space perform equivalently when compared to models trained on all data. Through 10-fold cross-validation on a comprehensive set containing 67,950 of our company's proprietary analytes, these models achieved coefficients of determination of 0.84 and 3 % error in terms of retention time. This promising statistical significance is found to translate from cross-validation to prospective prediction on an external test set of pharmaceutically relevant analytes. The observed equivalency of global and local modeling of large datasets is retained with METLIN's SMRT dataset, thereby confirming the wider applicability of the developed machine learning workflows for global models.

[Research Progress on Pollution Characteristics, Degradation, and Transformation of Typical PPCPs in the Process of Wastewater Treatment].

Pharmaceuticals and personal care products (PPCPs) have received extensive attention as a new type of pollutant inin the 21st century, and the ecological and health risks caused by PPCPs have gradually been recognized by government regulatory agencies. Daily use of PPCPs has led to their frequent detection and high concentrations in the influent, effluent, and sludge of wastewater treatment plants, but traditional wastewater treatment processes can't remove them effectively. Most research about enhancing the removal of PPCPs through microbial degradation, photodegradation, and ozonation is still in the laboratory research stage, and the removal effects are not satisfactory when applied to actual sewage treatment. Therefore, the effective removal of PPCPs from domestic wastewater is a critical technical problem that urgently needs to be studied and solved in the coming years. At present, many scholars do not have a comprehensive understanding about the degradation and transformation behaviors of microbes, ultraviolet, and ozone for typical PPCPs in the wastewater treatment process, so it is necessary to conduct a systematic analysis and discussion. In this study, 16 typical PPCPs frequently detected in sewage treatment plants were selected as research objects through a literature review. The occurrence, removal characteristics, and sludge adsorption properties of typical PPCPs in wastewater treatment plants were analyzed and summarized. The degradation and transformation behavior of typical PPCPs under microbial, ultraviolet, and ozone treatments in the wastewater treatment process were also discussed. Finally, based on current research gaps, some research directions for the removal and transformation of PPCPs in wastewater were proposed:① investigation into the removal characteristics of PPCPs by actual biochemical treatment; ② study on the mechanism of microbial degradation and transformation of typical PPCPs during biochemical treatment; ③ study on the degradation and transformation mechanism of typical PPCPs by UV/ozone in an actual sewage system; and ④ research on the application technology of removing PPCPs from sewage via microbial degradation, photodegradation, ozone oxidation, etc. The relevant results of this study can provide a reference for the pollution control of typical PPCPs in the sewage treatment process.

Large-Scale Screening of Pharmaceutical Compounds to Explore the Application Space of On-Tissue MALDI and MALDI-2 Mass Spectrometry.

The successful application of matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) in pharmaceutical research is strongly dependent on the detection of the drug of interest at physiologically relevant concentrations. Here we explored how insufficient sensitivity due to low ionization efficiency and/or the interaction of the drug molecule with the local biochemical environment of the tissue can be mitigated for many compound classes using the recently introduced MALDI-MSI coupled with laser-induced postionization, known as MALDI-2-MSI. Leveraging a MALDI-MSI screen of about 1,200 medicines/drug-like compounds from a broad range of medicinal application areas, we demonstrate a significant improvement in drug detection and the degree of sensitivity uplift by using MALDI-2 versus traditional MALDI. Our evaluation was made under simulated imaging conditions using liver homogenate sections as substrate, onto which the compounds were spotted to mimic biological conditions to the first order. To enable an evaluable detection by both MALDI and MALDI-2 for the majority of employed compounds, we spotted 1 µL of a 10 mM solution using a spotting robot and performed our experiments with a Bruker timsTOF fleX MALDI-2 instrument in both positive and negative ion modes. Specifically, we demonstrate using a large cohort of drug-like compounds that ∼60% of the tested compounds showed a more than 10-fold increase in signal intensity and ∼16% showed a more than 100-fold increase upon use of MALDI-2 postionization. Such increases in sensitivity could help advance pharmaceutical MALDI-MSI applications toward the single-cell level.

Rapid Separation and Detection of Drugs in Complex Biological Matrix Using TD-CDI Mass Spectrometer.

The drug detection technology plays a pivotal role in the domains of pharmaceutical regulation and law enforcement. In this study, we introduce a method that combines thermal desorption corona discharge ionization (TD-CDI) with mass spectrometry for efficient drug detection. The TD-CDI module, characterized by its compact and simple design, enables the separation of analytes within seconds and real-time presentation of one or two analyte peaks on the mass spectrum most of the time, which reduces matrix interference and improves detection performance. Through experimental investigation, we studied the characteristics of TD-CDI for analyte separation and detection, even with the same mass number, and optimized the TD-CDI approach. TD-CDI-MS was employed for the rapid detection of drugs in various traditional medicine, food products, and human samples. Additionally, by utilizing TD-CDI for segmented hair direct analysis, it becomes possible to trace the drug usage cycle of individuals. This underscores the feasibility of the proposed analytical method within the realm of drug detection.

Microchip isotachophoresis for green and sustainable pharmaceutical quality control: Method validation and application to complex pharmaceutical formulations.

Universal microchip isotachophoresis (µITP) methods were developed for the determination of cationic and anionic macrocomponents (active pharmaceutical ingredients and counterions) in cardiovascular drugs marketed in salt form, amlodipine besylate and perindopril erbumine. The developed methods are characterized by low reagent and sample consumption, waste production and energy consumption, require only minimal sample preparation and provide fast analysis. The greenness of the proposed methods was assessed using AGREE. An internal standard addition was used to improve the quantitative parameters of µITP. The proposed methods were validated according to the ICH guideline. Linearity, precision, accuracy and specificity were evaluated for each of the studied analytes and all set validation criteria were met. Good linearity was observed in the presence of matrix and in the absence of matrix, with a correlation coefficient of at least 0.9993. The developed methods allowed precise and accurate determination of the studied analytes, the RSD of the quantitative and qualitative parameters were less than 1.5% and the recoveries ranged from 98 to 102%. The developed µITP methods were successfully applied to the determination of cationic and anionic macrocomponents in six commercially available pharmaceutical formulations.

Application of deep UV resonance Raman spectroscopy to column liquid chromatography: Development of a low-flow method for the identification of active pharmaceutical ingredients.

In this study, deep UV resonance Raman spectroscopy (DUV-RRS) was coupled with high performance liquid chromatography (HPLC) to be applied in the field of pharmaceutical analysis. Naproxen, Metformin and Epirubicin were employed as active pharmaceutical ingredients (APIs) covering different areas of the pharmacological spectrum. Raman signals were successfully generated and attributed to the test substances, even in the presence of the dominant solvent bands of the mobile phase. To increase sensitivity, a low-flow method was developed to extend the exposure time of the sample. This approach enabled the use of a deep UV pulse laser with a low average power of 0.5 mW. Compared to previous studies, where energy-intensive argon ion lasers were commonly used, we were able to achieve similar detection limits with our setup. Using affordable lasers with low operating costs may facilitate the transfer of the results of this study into practical applications.