Background and purpose: Quality by design (QbD) has revolutionized pharmaceutical development by shifting from a conventional quality-by-testing approach to a science-based approach that incorporates quality into products and processes from inception. The integration of artificial intelligence (AI), machine learning (ML), automation, and digital technologies with QbD offers new opportunities to enhance process understanding, optimize critical quality attributes (CQAs) and support the Pharma 4.0 industry framework. Experimental approach: A systematic review of studies published between 2016 and 2025 was conducted to evaluate the application of supervised learning algorithms, deep neural networks, reinforcement learning, and digital twin technologies within QbD. Regulatory frameworks, including International Council for Harmonisation (ICH) quality guideline Q8 through Q14, the U.S. Food and Drug Administration’s Emerging Technology Program and the European Medicines Agency quality initiative, together with representative industrial case studies, were also examined. Key results: This review demonstrates that AI-driven QbD improves process understanding, CQA optimization, batch-to-batch consistency, process robustness, and real-time quality control. Further, advanced computational models enable predictive process monitoring, intelligent decision-making, and in silico experimentation, reducing manufacturing costs, development time and experimental burden. However, challenges related to data quality, model interpretability, validation, and regulatory harmonisation remain a critical barrier to widespread implementation. Conclusion: The convergence of AI, ML and QbD provides a robust framework for intelligent pharmaceutical manufacturing (PM). AI-enabled QbD supports the development of high-quality products through predictive, data-driven, and in silico approaches while accelerating development and improving manufacturing efficiency. These technologies offer a practical roadmap toward Pharma 4.0 and the future of digital PM.
Background and purpose: The simultaneous determination of acetaminophen (ACE) and ciprofloxacin (CIP) is of considerable importance for pharmaceutical quality control, necessitating the development of sensitive and reliable electrochemical sensors. In this study, a holmium-modified UiO-66 metal-organic framework (Ho/UiO-66) was synthesized and evaluated as an electrode modifier for the simultaneous electrochemical determination of ACE and CIP. Experimental approach: Ho/UiO-66 was synthesized via a solvothermal method and characterized by X-ray diffraction, Fourier-transform infrared spectroscopy, Raman spectroscopy, nitrogen adsorption-desorption analysis, scanning electron microscopy, transmission electron microscopy and energy-dispersive X-ray mapping. The electrochemical behaviour of ACE and CIP at the Ho/UiO-66-modified glassy carbon electrode (Ho/UiO-66/GCE) was investigated using cyclic voltammetry and differential pulse voltammetry. The effects of solution pH, scan rate, accumulation potential, and accumulation time were systematically optimized. Key results: The characterization results demonstrated the successful incorporation of Ho species while preserving the crystalline structure of UiO-66. Among the investigated materials, Ho/UiO-66 (3/100 molar ratio) exhibited the most favourable combination of crystallinity, porosity and electrochemical performance, and was therefore selected for sensor fabrication. Under the optimized conditions, well-resolved oxidation peaks for ACE and CIP were obtained, enabling their simultaneous determination without mutual interference. The oxidation processes were found to be predominantly diffusion-controlled. The developed sensor exhibited satisfactory analytical performance with wide linear concentration ranges, low detection limits, satisfactory repeatability, reproducibility, and long-term stability. The sensor was applied to the determination of ACE and CIP in real pharmaceutical samples with satisfactory recoveries. The analytical results showed good agreement with those obtained using the reference high-performance liquid chromatography method. Conclusion: The proposed Ho/UiO-66/GCE sensor provides a reliable and practical platform for the simultaneous electrochemical determination of ACE and CIP, demonstrating its potential applicability for pharmaceutical analysis.
Background and purpose: Erlotinib (ERL), a first-generation epidermal growth factor receptor tyrosine kinase inhibitor drug that is used in non-small cell lung cancer treatment, requires precise therapeutic drug monitoring owing to its narrow therapeutic window and significant inter-patient pharmacokinetic variability; existing chromatographic methods, while robust, are resource-intensive and incompatible with point-of-care settings, necessitating the development of simpler, cost-effective electroanalytical alternatives. Experimental approach: A titanium dioxide nanoparticle-modified screen-printed electrode (TiO₂NP@SPE) was fabricated via a facile single-step modification and comprehensively characterized by scanning electron microscopy - energy dispersive X-ray Analysis, Fourier transform infrared spectroscopy, X-ray diffraction and electrochemical impedance spectroscopy; electrochemical performance was evaluated by cyclic voltammetry and differential pulse voltammetry, and analytical validation was performed in human serum using the standard addition method. Key results: The TiO₂NP@SPE demonstrated markedly enhanced electron transfer kinetics over the bare SPE, yielding a well-defined linear response with a competitive limit of detection, high sensitivity, and intra- and inter-day serum recoveries within acceptable precision limits, alongside excellent selectivity against physiologically relevant interferents and structurally related anticancer agents. Conclusion: This work developed a disposable screen-printed electrode sufficient to achieve sensitive, selective, and accurate quantification of ERL in human serum using TiO₂NP@SPE as a promising, clinically translatable platform for point-of-care therapeutic drug monitoring in oncology; future efforts should address the elevated detection limit relative to the bare electrode and extend validation to real patient plasma samples to fully confirm clinical applicability.
Background and purpose:Calcium folinate (CFT) is a medication used as an antidote to methotrexate (MTT) and as a vitamin against anaemia. MTT is used to treat a variety of carcinomas, including acute lymphoblastic leukaemia, head and neck cancer, gastric cancer, breast cancer and choriocarcinoma. Experimental approach:A nanocomposite made of Fe and Mg linked to a 1,4-benzene dicarboxylate ligand metal organic framework (FeMg-BDC MOF) was created for this investigation. Using field emission scanning electron microscopy, the morphology and structure of the Mg-BDC MOF were examined. Next, a screen-printed electrode modified with a synthetic nanocomposite (FeMg-BDC MOF/SPE) was used as the working electrode for voltammetric detection of CFT. Key results:The FeMg-BDC MOF/SPE demonstrated high electrocatalytic activity for CFT oxidation as compared to unmodified SPE. The limit of detection is 0.04 μM, and under ideal conditions, the oxidation peak currents of CFT show a linear relationship with its concentration in the range of 0.1 to 390.0 μM. Additionally, when MTT was present, the FeMg-BDC MOF/SPE demonstrated good activity toward CFT determination. The separation of the oxidation peak potentials (255 mV) indicates that differential pulse voltammetry can be used to detect these two medications simultaneously. Conclusion:The devised sensor's applicability was confirmed with outstanding results using CFT and MTT assays in pharmaceutical specimens and urine samples.
Background and purpose: Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) have emerged as a promising cell-free therapy for osteoarthritis (OA). However, their transition into clinical therapeutics is constrained by unstandardized pharmacokinetics and heterogeneous preclinical reporting. Experimental approach: A meta-analysis of preclinical in vivo OA models evaluating MSC-EV therapy was conducted. Study quality was rigorously assessed using MISEV 2023 (Minimal Information for Studies of Extracellular Vesicles, 2023) criteria and the SYRCLE (Systematic Review Centre for Laboratory animal Experimentation) risk-of-bias tool. Quantitative synthesis was performed for the Osteoarthritis Research Society International (OARSI) histological score, reporting pooled mean differences (MDs) and 95 % confidence intervals (95% CIs), along with heterogeneity (I² statistic) and microRNA (miRNA) cargo analysis. Key results: MSC-EV administration conferred robust structural protection against cartilage degradation. Quantitative synthesis of human-derived MSC-EVs (26 studies) significantly reduced OARSI scores (MD -3.27, 95% CI -4.66 to -1.88; p < 0.0001). Similarly, quantitative synthesis of animal-derived MSC-EVs (8 studies) demonstrated an even more profound effect (MD -5.58, 95% CI -7.13 to -4.03; p < 0.0001). Non-parametric Trim-and-Fill analysis estimated zero missing studies in both datasets, confirming that these effect sizes are highly robust to publication bias. Despite these robust efficacy signals, significant heterogeneity (I² > 84 %) persisted. Meta-regression revealed that arbitrary dosage metrics, whether reported by particle count or protein concentration, failed to reliably predict treatment efficacy, highlighting severe gaps in dose-exposure standardization. Conclusion: MSC-EVs demonstrate highly potent, cross-species efficacy in attenuating OA progression. However, clinical translation is critically bottlenecked by a lack of ADMET (absorption, distribution, metabolism, excretion and toxicity) compliance. Future research must prioritize standardized particle-based dosing, in vivo pharmacokinetic tracking, and rigorous cargo-function validation to enable regulatory approval.
Background and purpose: Sibutramine is a synthetic anti-obesity drug that has been banned or restricted in many countries due to serious cardiovascular risks. However, its illegal adulteration in herbal weight-loss products remains a public health concern. This study aimed to develop a simple, sensitive, and reliable electrochemical method for the determination of sibutramine in herbal weight-loss products using a silver-nanoparticle-electrochemically reduced graphene oxide modified glassy carbon electrode. Experimental approach: Graphene oxide, electrochemically reduced graphene oxide, silver nanoparticles and AgNPs-ErGO nanocomposite were synthesized and characterized using X-ray diffraction, Fourier-transform infrared spectroscopy, scanning electron microscopy combined with energy dispersive X-ray spectroscopy, Raman spectroscopy and high-resolution transmission electron microscopy. The AgNPs-ErGO-modified glassy carbon electrode was fabricated and used for sibutramine detection by linear sweep voltammetry. Experimental parameters affecting the analytical signal were optimized. The method was validated according to AOAC guidelines and compared with an HPLC-DAD reference method. Key results: The AgNPs-ErGO/GCE exhibited improved electrochemical response toward sibutramine compared with bare and other modified electrodes. The developed method showed good selectivity, linearity, precision, accuracy, and sensitivity for sibutramine determination. Application to commercial herbal weight-loss samples demonstrated the suitability of the proposed method for real sample analysis, with results comparable to those obtained by HPLC-DAD. Conclusion: The AgNPs-ErGO/ /GCE-based electrochemical method provides a rapid, cost-effective, and reliable approach for detecting sibutramine adulteration in herbal weight-loss products. This work contributes to the development of practical analytical tools for quality control and consumer safety monitoring.
Background and purpose: Bile salt export pump (BSEP) inhibition is a key mechanistic driver of cholestatic drug-induced liver injury, yet current prediction approaches rely mainly on in vitro potency and calculated physicochemical descriptors that do not adequately reflect local exposure at the canalicular membrane. This study aimed to evaluate whether biomimetic chromatographic descriptors could improve predictions of BSEP inhibition by incorporating mechanistically relevant information on membrane affinity and protein binding. Experimental approach: A dataset of 62 structurally diverse compounds with reported BSEP inhibition data was compiled and modelled using multiple linear regression. Biomimetic descriptors derived from immobilized artificial membrane chromatography and human serum albumin affinity (log kHSA) were compared against conventional descriptors such as lipophilicity and molecular weight. Model performance was assessed using internal and external validation, graphical diagnostics, Y-randomization, and applicability domain analysis. Key results: Models based on biomimetic descriptors demonstrated superior, more balanced predictive performance than conventional physicochemical models, with greater robustness and external predictivity. The combination of membrane-affinity and protein-binding descriptors provided a more accurate representation of the determinants governing BSEP interactions. Conclusion: Biomimetic chromatographic descriptors provide an experimentally grounded approximation of membrane-proximal exposure, a key determinant of BSEP interactions that conventional descriptors do not capture. This approach extends beyond traditional quantitative structure-activity relationship by incorporating distribution-relevant properties into predictive modelling and offers a simple, interpretable framework to support early identification of transporter-mediated toxicity risk in drug discovery.
Background and purpose: Acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) are crucial enzymes implicated in various neurological disorders, including Alzheimer’s disease. Developing selective inhibitors for either enzyme is one of the key therapeutic strategies. This study aimed to synthesize and evaluate a novel series of peptidomimetics for their ability to inhibit both human AChE and BChE, with a focus on identifying compounds exhibiting joint inhibitory activity or selectivity for BChE. Experimental approach: Eleven peptidomimetics were synthesized using the Ugi four-component reaction. In vitro enzyme inhibition assays were performed to determine the dissociation constants (Ki) for both human AChE (hAChE) and human BChE (hBChE). Principal component analysis was employed to analyse the inhibition data and map compound selectivity. To investigate the molecular interactions between the peptidomimetics and the BChE active site, quantum-chemical docking simulations were conducted. Key results: All synthesized compounds exhibited reversible, micromolar inhibition of both hAChE and hBChE. Two compounds demonstrated significant BChE selectivity, with 279- and 169-fold higher preference for BChE, respectively. Principal component analysis revealed distinct clusters correlating with preferential binding to either enzyme. Docking simulations supported these findings, highlighting key stabilizing interactions (primarily π-π stacking) between the peptidomimetics and BChE, explaining superior selective and joint inhibitory activity. Conclusion: This work demonstrates the successful synthesis and characterization of novel peptidomimetics with varying degrees of hAChE and hBChE inhibition, including compounds with notable BChE selectivity. The combination of experimental data and computational modelling provides valuable insights into the structural basis of enzyme inhibition and establishes a foundation for rational design of more potent and selective cholinesterase inhibitors based on the designed scaffold.
Background and purpose: Cancer is one of the most life-threatening diseases and has the highest mortality rate worldwide. Delayed cancer diagnosis remains a major challenge in cancer treatment. Currently, conventional diagnostic methods still have several limitations, resulting in many cancer cases being detected only at advanced stages. Experimental approach: This review was conducted as a literature study of research on the development of affibody-based biosensors for cancer biomarker detection. The review discusses the characteristics of affibodies as bioreceptors, affibody synthesis methods, and their applications in electrochemical and optical biosensors. Key results: Various studies have shown that affibody-based biosensors exhibit high sensitivity and specificity for detecting cancer biomarkers such as human epidermal growth factor receptor 2, tumour necrosis factor-alpha, epidermal growth factor receptor, carcinoembryonic antigen and alpha-fetoprotein. The integration of affibodies into biosensor platforms enables low detection limits, wide linear ranges and good analytical performance in biological samples. Conclusion: Affibody-based biosensors show great potential as platforms for cancer diagnosis. The use of affibodies as bioreceptors offers several advantages over antibodies and aptamers, particularly ease of synthesis, high stability and strong binding affinity.
Background and purpose: Tuberculosis (TB), a serious global health concern, continues to contribute to the global health burden, underscoring the urgent need to discover potent antitubercular agents. In the present study, a series of novel 5,6-diphenyl-1,2,4-triazine-piperazine derivatives were synthesized, and their potential for anti-tubercular activity was assessed. Experimental approach: The antitubercular potential of the synthesized compounds was assessed using the microplate alamar blue assay (MABA). Cytotoxicity studies were carried out on RAW 264.7 macrophages. To assess the mode of action of the synthesized compounds, docking analysis of the active compounds was performed on two key enzymes of Mycobacterium, decaprenylphosphoryl-β-D-ribose 2′-epimerase and Mycobacterium tuberculosis-dihydrofolate reductase (Mtb-DHFR). Furthermore, molecular dynamics simulations and density functional theory calculations were performed to validate the stability of the ligand–protein complexes and the electronic properties of the lead compounds. Key results: The results revealed promising anti-tubercular activity for the synthesized compounds. Among these, compounds 2-((5,6-Diphenyl-1,2,4-triazin-3-yl)thio)--1-(4-(4-fluorobenzoyl)piperazin-1-yl)ethan-1-one (FP3) and 2-((5,6-diphenyl-1,2,4-triazin-3-yl)thio)-1-(4-(4-methylbenzoyl) piperazin-1-yl)ethan-1-one (FP8) exhibited potent activity with an minimum inhibitory concentration of 1.6 µg mL⁻¹, along with promising cytotoxicity profiles against RAW 264.7 macrophage cells. Docking studies revealed potent docking scores compared to the standard, thereby confirming the involvement of the DHFR enzyme. Interaction analysis revealed stable hydrogen-bond interactions, π-π stacking, and hydrophobic interactions with the active-site residues of the DHFR enzyme. Additionally, molecular dynamics simulation validated the stability of the interactions and the structural integrity of the complexes, while density functional theory calculations supported the desirable electronic properties of the lead compounds. Conclusion: The combined results of the experiments and calculations validated the potential of FP3 and FP8 as DHFR-targeted antitubercular agents. The study highlights the potential of 5,6-diphenyl-1,2,4-triazine-piperazine derivatives as promising candidates for further anti-tubercular drug development.
Background and purpose: Cancer chemotherapy with antineoplastic drugs destroys cancer cells through complete cell death or stops cell development while protecting healthy cells from damage. Monitoring anticancer therapeutics in blood and tissues is important for determining their fate. Experimental approach: A novel binuclear complex with the formula [Cu(opd)2(H2O)(μ-SCN)Ni(opd)(SCN)3] (opd = o-phenylenediamine) was synthesized and characterized using Fourier transform infrared spectroscopy and UV-Vis spectroscopy. The solvothermal method was used to create a nanoscale version of the binuclear complex. X-ray powder diffraction, scanning electron microscopy, UV-Vis and FT-IR spectroscopy were used to characterize the nanocomplex. The solvothermal approach produced a nanocomplex with an average size of around 56 nm. The complex was tested for its antimicrobial properties on Gram-positive Staphylococcus aureus and Enterococcus faecalis, as well as Gram-negative Escherichia coli and Pseudomonas aeruginosa. Additionally, a screen-printed graphite electrode modified by a synthetic nanocomplex (Cu-Ni/SPGE) was presented as an improved electrochemical sensor for the detection of idarubicin (IRN). Key results: This sensor has a linear dynamic range from 0.01 to 3.0 μM and an impressive limit of detection of 0.003 μM under ideal testing circumstances. Conclusion: The researchers used a Cu-Ni/SPGE system to perform electrochemical measurements on IRN. The Cu-Ni/SPGE outperformed the untreated SPGE in terms of IRN oxidation. The antibacterial activity of the complex was also studied.
Background and purpose:The toxicity of organophosphorus compounds (OPs) and related nerve agents (NAs) impairs the cholinergic system via irreversible inhibition of acetylcholinesterase (AChE) activity by phosphylation of the catalytic serine. Reactivation of the enzyme activity largely depends on the structural compatibility between the enzyme, an oxime reactivator, and the specific OP compound. Experimental approach:For this study, we used our recently published data on the reactivation of human butyrylcholinesterase inhibited by the NAs sarin, cyclosarin, tabun and VX, using a library of 115 oximes. We compared these results with oximes' ADME (absorption, distribution, metabolism, and excretion) parameters relevant to central nervous system activity using principal component analysis (PCA). PCA facilitated the examination of these relatively large datasets by increasing interpretability while minimizing information loss. Key results:Three components with eigenvalues above 1 resulted in 72 % of the cumulative proportion of variance and described 27 variables. PC1 created transformed data that had negative values for most oximes with high reactivation potential, while showing large positive values for oximes with moderate and low efficacy. Distribution of 27 loadings, representing 27 variables, produced a set of 9 positive and 18 negative loadings representing negative and positive data correlation. The efficacy of oxime reactivation was highly correlated with the parameters describing its structure: molecular weight, rotational bonds, molecular volume, and molecular surface area. Conclusion:A large dataset was efficiently analysed by maximizing the preservation of variability and generating new, uncorrelated variables. To our knowledge, this study is the first to apply PCA to assess oxime's reactivation efficacy, thus providing insights into the relationships between oxime properties and their efficacy in restoring OP-inhibited cholinesterase activity.
Background and purpose:Ocular inflammation is a key challenge after ocular surgery, and resistance has developed in the bacterial strain. Primarily, the short residence time of the ocular formulation makes it more effective in treating and alleviating inflammation. Experimental approach:In this study, a moxifloxacin-incorporated gum ghatti-infused poly(vinyl alcohol-chitosan) polymeric film was developed by solvent casting. Various properties of the ocular composite film, including mucoadhesiveness, strength profile, and crystal size, were evaluated. Key results:The prepared composite film exhibited a red-yellow hue. XRD and DSC analyses revealed that the drug in the formulation is amorphous. The release profile reduces the release rate and follows both Fickian- and non-Fickian-mediated pathways. A clear zone of inhibition was observed against both Gram-negative (Pseudomonas aeruginosa) and Gram-positive (Staphylococcus aureus) bacteria. The in vivo anti-inflammatory potential of carrageenan was observed against the prepared formulations, and within 1.5 hours, redness and inflammation diminished. Corneal integrity was maintained, with no dark spots observed in the corneal region, confirming that no coagulant or thrombosis of blood occurred in the eye. Conclusion:Based on the foregoing discussion, the formulation shows potential for treating ocular conjunctivitis and can be safely used for pink eye, bacterial conjunctivitis, or allergic conjunctivitis.
Background and purpose: Neurodegenerative disorders such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) pose an escalating challenge to neuroscience, as disease-modifying therapies remain elusive despite substantial advances in molecular and cellular understanding. These disorders share convergent pathological features, including protein misfolding and aggregation, mitochondrial dysfunction, oxidative stress, impaired proteostasis, and disruption of circadian regulation. Identifying integrative frameworks that connect these processes is therefore essential for advancing conceptual models of neurodegeneration. This review examines magneto-proteins, with a particular focus on CRY/MagR-based magnetoreceptor complexes, as emerging biological systems that may intersect with key molecular pathways implicated in AD and PD. Experimental approach: We synthesized literature from neuroscience, biophysics, and circadian biology to evaluate the potential relevance of magnetoreceptor mechanisms to AD and PD pathology. We first summarized the core neuropathological mechanisms underlying both diseases, including amyloid-β and tau pathology in AD and α-synuclein aggregation and dopaminergic vulnerability in PD. We then outlined the biophysical foundations of magneto-protein function, emphasizing cryptochrome-mediated radical pair mechanisms, iron-sulfur cluster-dependent magnetic sensitivity, and their established roles in redox signaling and circadian biology. Key results: Accumulating experimental evidence from cellular and animal models suggests that CRY/MagR-associated pathways can modulate oxidative stress, mitochondrial bioenergetics, protein aggregation dynamics, autophagic processes, and circadian control of neuronal metabolism. These processes closely overlap with molecular determinants of neuronal vulnerability in AD and PD. However, direct validation in mammalian and human systems remains limited and controversial, representing a critical knowledge gap. Conclusion: The mechanistic convergence between magnetoreceptor biology and neurodegenerative pathology warrants critical evaluation but remains largely speculative in humans. By integrating findings across disciplines, this review positions CRY/MagR-based magneto-proteins as a conceptual platform for exploring how magnetic field-responsive molecular systems may inform our understanding of neurodegenerative disease mechanisms, while emphasizing the need for rigorous mammalian validation.
Background and purpose New Delhi Metallo beta-lactamase-1 (NDM-1) is a zinc-dependent enzyme that confers resistance to several antibiotics; therefore, there is an urgent requirement for effective inhibitors. Captopril has been exploited as a scaffold in the design of NDM-1 inhibitors; however, a comparative evaluation of these derivatives from structure activity relationship perspective has not been conducted. This review aimed to evaluate captopril-derived NDM-1 inhibitors and to identify possible structure-activity relationships that govern their NDM-1 inhibitory action. Experimental approach: The literature was searched in a structured manner using scholarly databases to locate original studies that reported captopril derivatives and evaluated them in vitro against NDM-1 with the explicit reporting of the inhibitory concentration values (IC50). Eligible studies were filtered using predefined criteria and analysed using a qualitative approach, because heterogeneity in assay conditions and experimental methods prevented a direct quantitative comparison across studies. Important findings: The activity of captopril derivatives depends on the free thiol group (masking it reduces activity), with stereochemistry governing optimal binding orientation within the NDM-1 active site, hydrophobic substitutions enhance activity only within steric limits, and the carboxylate motif serves as a secondary anchoring feature. Conclusion: Captopril emerges as a promising scaffold for NDM-1 inhibitors and reveals significant structural features associated with NDM-1 inhibitors. Despite limited in vivo data and heterogeneity in assay conditions, the findings provide a rational framework for optimizing captopril-inspired NDM-1 inhibitors.
Background and purpose: Epinephrine, also called noradrenaline, is an important chemical mediator in the central nervous system of mammals. Experimental approach: The hydrothermally synthesized NiO nanostructures were used for the modification of a screen-printed electrode, and they were characterized and used in this work for the voltammetric determination of epinephrine in the presence of acetaminophen. Several electrochemical techniques were employed to investigate the electrochemical properties of NiO-modified screen-printed carbon electrode, including cyclic voltammetry, differential pulse voltammetry and chronoamperometry. Key results: The differential pulse voltammetry peak current of epinephrine was linear with concentration in the range from 0.01 to 400.0 μmol L-1, and the limit of detection was 0.005 μM with a sensitivity of 0.1167 μA L μmol-1. The findings indicated that the current signals for epinephrine were significantly amplified, a result attributed to the superior catalytic performance of the NiO nanostructures. Furthermore, the oxidation peaks for epinephrine and acetaminophen were distinctly separated, with potential differences of approximately 360 mV and 545 mV, respectively. Conclusion: Furthermore, the NiO modified screen-printed carbon electrode was successfully applied to quantify epinephrine and acetaminophen in both urine samples and pharmaceutical formulations. The results indicated satisfactory recovery rates for the target analytes. Consequently, this electrode is suitable for the analysis of both compounds in pharmaceutical and clinical laboratory settings.
Background and purpose: The central nervous, renal, hormonal, and cardiovascular systems depend on dopamine. Therefore, a straightforward, sensitive, and selective method for detecting DA is needed to track DA levels in the human body. Experimental approach: Co/Ni-metal-organic framework was developed via a one-pot hydrothermal synthesis. The electrochemical sensor developed for dopamine measurement used Co/Ni-metal-organic framework materials on screen-printed carbon electrodes. The Co/Ni-metal-organic framework on a screen-printed carbon electrode exhibits excellent electrocatalytic activity for dopamine oxidation, owing to its high electron-transfer rate. Key results: The electrocatalytic activity of Co/Ni-metal-organic framework on a screen-printed carbon electrode significantly improves dopamine oxidation, yielding higher peak currents and lower oxidation potentials than the bare screen-printed carbon electrode. The sensor detected dopamine with a linear response, ranging from 0.01 to 660.0 µmol L-1, with a limit of detection of 0.007 µmol L-1. To measure tyrosine and dopamine simultaneously, differential pulse voltammetry was used. The separation between tyrosine and dopamine reached 150 mV. Conclusion: Successful target-analyte identification using the proposed voltammetric sensor was achieved, detecting both dopamine and tyrosine in actual sample tests.
Background and purpose: Tamoxifen is a cornerstone of adjuvant endocrine therapy for breast cancer, yet significant inter-individual variability in treatment response and mortality exists. Identifying robust predictors of outcomes remains a critical need. This study integrated machine learning, explainable artificial intelligence (XAI) and Bayesian modelling to predict mortality and identify key prognostic factors in breast cancer patients receiving adjuvant tamoxifen. Experimental approach: We analysed data from 568 patients from the International Tamoxifen Pharmacogenomics Consortium database. The outcome was all-cause mortality, with predictors including age, race, menopausal status, tumour size, estrogen receptor status, radiation treatment, and CYP2D6 metabolizer status. Four algorithms, logistic regression, random forest, eXtreme Gradient Boosting (XGBoost) and support vector machine, were developed and validated. Model performance was assessed using accuracy and area under the receiver operating characteristic curve (AUC). SHapley Additive exPlanations (SHAP) analysis provided interpretability for the XGBoost model, and Bayesian logistic regression with weakly informative priors was employed for probabilistic inference. Key results: The overall mortality rate was 19.4 %. XGBoost demonstrated the highest discriminative ability (AUC 0.833; 95 % confidence interval: 0.725 to 0.941), while random forest exhibited superior sensitivity for identifying deceased patients (83.3 %). SHAP analysis revealed that white race, increased age, absence of radiation treatment, larger tumour size and the CYP2D6 poor metabolizer (PM/PM) genotype were associated with elevated mortality risk, whereas the extensive metabolizer (EM/EM) genotype was protective. Significant variability was observed in exploratory subgroup analyses, with the model achieving excellent discrimination in patients without radiation treatment (AUC 0.901) and those with the EM/PM genotype (AUC 0.956) but failing to identify any mortality events in the Caucasian subgroup. Bayesian logistic regression yielded comparable performance to frequentist methods (AUC 0.820), with tumour size emerging as a consistently strong predictor in partial dependence plots. Conclusion: Integrating machine learning with XAI and Bayesian approaches effectively identified key predictors of mortality in tamoxifen-treated breast cancer patients. However, marked heterogeneity in model performance across subgroups highlights the critical need for external validation and careful evaluation of algorithmic fairness before clinical implementation.
Background and purpose: The steady-state volume of distribution reflects the extent to which drugs partition between plasma and tissues and is closely related to the tissue-to-plasma partition coefficient. In pharmacokinetics, different modelling frameworks have led to ongoing debate regarding the role of plasma protein binding and the importance of unbound drug exposure in determining both distribution and clearance. This review aims to clarify the relationship between distribution and elimination models and to assess how experimental binding measurements can support their mechanistic interpretation. Experimental approach: Established pharmacokinetic relationships linking volume of distribution (Vd), clearance and half-life were analysed alongside biomimetic chromatographic measurements of drug binding to human serum albumin and phospholipid membranes using immobilized artificial membrane (IAM) chromatography. Literature data for marketed drugs were evaluated to examine how these experimental descriptors relate to distribution and clearance behaviour. Key results: The analysis shows that distribution and clearance models describe complementary aspects of drug disposition rather than contradictory processes. Tissue binding, as reflected by phospholipid affinity measured by IAM chromatography, plays a dominant role in determining Vd, while plasma protein binding influences both distribution and clearance through its effect on the fraction of drug unbound in plasma. The apparent paradox of plasma protein binding arises because changes in unbound fraction affect both processes simultaneously. Conclusion: This work demonstrates that biomimetic binding measurements provide a mechanistically meaningful bridge between physicochemical properties and pharmacokinetic behaviour. By integrating experimental binding data with pharmacokinetic models, the study advances understanding of how distribution and clearance are linked, supporting more informed decision-making in early drug discovery while highlighting that clearance remains influenced by additional factors beyond non-specific binding.
Background and purpose: The primary objective of this study was to assess the feasibility of applying in situ UV spectroscopy in combination with multicomponent analysis (MCA) to simultaneously quantify the dissolution of a drug and its coformer from a cocrystal. A secondary objective was to determine whether this approach can support a mechanistic understanding of cocrystal dissolution. Experimental approach: The rotating-vessel μDISS system equipped with an in situ UV probe was used for dissolution tests. Carbamazepine (CBZ) cocrystals with saccharin, nicotinamide, and 2,4-dihydroxybenzoic acid were used as model compounds. The concentrations of CBZ and each coformer were simultaneously quantified using MCA of the in situ UV spectra. Key results: The concentrations of CBZ and the coformer were successfully quantified by MCA throughout the dissolution process. In the absence of a polymeric precipitation inhibitor (PPI), the dissolution of CBZ from the cocrystal reached only 20%, and no supersaturation was observed, whereas the coformers were rapidly released. In contrast, in the presence of PPIs, the dissolution of CBZ from the cocrystal increased to supersaturated levels, while the dissolution of the coformer decreased. Supersaturation of CBZ was achieved when CBZ and the coformer dissolved congruently. A PPI may interfere with the molecular dissociation of CBZ and the coformer from the cocrystal surface, resulting in a slower release of both CBZ and the coformer. This effect may have reduced the local CBZ concentration at the particle surface and, consequently, slowed the precipitation of CBZ dihydrate on the particle surface. Conclusion: MCA enables the simultaneous quantification of a drug and its coformer from in situ UV spectra during cocrystal dissolution testing. This analytical approach provides valuable insights into the dissolution mechanisms of cocrystals.
