Search Results (2,754)

The Caco-2 in vitro model of the intestinal barrier is a well-established system for the investigation of the intestinal fate of orally ingested chemicals and drugs, and it has been used for over ten years by pharmaceutical industries as a model for absorption in preclinical studies. The Caco-2 model shows a fair correlation with in vivo drug absorption, though some inherent biases remain unresolved. Its main limitation lies in the lack of structural complexity, as it does not replicate the diverse cell types and mucus layer present in the human intestinal epithelium. Consequently, the development of advanced in vitro models of the intestinal barrier, that more structurally resemble the human intestinal epithelium physiology, has increased the potential applications of these models. Recently, Caco-2-based advanced intestinal models have proven effective in predicting nanomaterial uptake and transport across the intestinal barrier. The aim of this review is to provide a state-of-the-art of human in vitro intestinal barrier models for the study of translocation/uptake of nanoparticles relevant for oral exposure, including inorganic nanomaterials, micro/nano plastic, and fiber nanomaterials. The main effects of the above-mentioned nanomaterials on the intestinal barrier are also reported. Full article

Background/Objectives. This manuscript presents an overview of advances in oncological radiotherapy as an effective treatment method for cancerous tumors, focusing on mechanisms of action within metabolite–antimetabolite systems. The urgency of this topic is underscored by the fact that cancer remains one of the leading causes of death worldwide: as of 2022, approximately 20 million new cases were diagnosed globally, accounting for about 0.25% of the total population. Given prognostic models predicting a steady increase in cancer incidence to 35 million cases by 2050, there is an urgent need for the latest developments in physics, chemistry, molecular biology, pharmacy, and strict adherence to oncological vigilance. The purpose of this work is to demonstrate the relationship between the nature and mechanisms of past diagnostic and therapeutic oncology approaches, their current improvements, and future prospects. Particular emphasis is placed on isotope technologies in the production of therapeutic nuclides, focusing on the mechanisms of formation of simple and complex theranostic compounds and their classification according to target specificity. Methods. The methodology involved searching, selecting, and analyzing information from PubMed, Scopus, and Web of Science databases, as well as from available official online sources over the past 20 years. The search was structured around the structure–mechanism–effect relationship of active pharmaceutical ingredients (APIs). The manuscript, including graphic materials, was prepared using a narrative synthesis method. Results. The results present a sequential analysis of materials related to isotope technology, particularly nucleus stability and instability. An explanation of theranostic principles enabled a detailed description of the action mechanisms of radiopharmaceuticals on various receptors within the metabolite–antimetabolite system using specific drug models. Attention is also given to radioactive nanotheranostics, exemplified by the mechanisms of action of radioactive nanoparticles such as Tc-99m, AuNPs, wwAgNPs, FeNPs, and others. Conclusions. Radiotheranostics, which combines the diagnostic properties of unstable nuclei with therapeutic effects, serves as an effective adjunctive and/or independent method for treating cancer patients. Despite the emergence of resistance to both chemotherapy and radiotherapy, existing nuclide resources provide protection against subsequent tumor metastasis. However, given the unfavorable cancer incidence prognosis over the next 25 years, the development of “preventive” drugs is recommended. Progress in this area will be facilitated by modern medical knowledge and a deeper understanding of ligand–receptor interactions to trigger apoptosis in rapidly proliferating cells. Full article

Background: Precision medicine refers to the formulation of personalized drug regimens according to the individual characteristics of patients to achieve optimal efficacy and minimize adverse reactions. Additive manufacturing (AM), also known as three-dimensional (3D) printing, has emerged as an optimal solution for precision drug delivery, enabling customizable and the fabrication of multifunctional structures with precise control over morphology and release behavior in pharmaceutics. However, the influence of 3D printing parameters on the printed tablets, especially regarding in vitro and in vivo performance, remains poorly understood, limiting the optimization of manufacturing processes for controlled-release profiles. Objective: To establish the fabrication process of 3D-printed controlled-release tablets via comprehensively understanding the printing parameters using fused deposition modeling (FDM) combined with hot-melt extrusion (HME) technologies. HPMC-AS/HPC-EF was used as the drug delivery matrix and carbamazepine (CBZ) was used as a model drug to investigate the in vitro drug delivery performance of the printed tablets. Methodology: Thermogravimetric analysis (TGA) was employed to assess the thermal compatibility of CBZ with HPMC-AS/HPC-EF excipients up to 230 °C, surpassing typical processing temperatures (160–200 °C). The formation of stable amorphous solid dispersions (ASDs) was validated using differential scanning calorimetry (DSC), hot-stage polarized light microscopy (PLM), and powder X-ray diffraction (PXRD). A 15-group full factorial design was then used to evaluate the effects of the fan speed (20–100%), platform temperature (40–80 °C), and printing speed (20–100 mm/s) on the tablet properties. Response surface modeling (RSM) with inverse square-root transformation was applied to analyze the dissolution kinetics, specifically t_50% (time for 50% drug release) and Q_4h (drug released at 4 h). Results: TGA confirmed the thermal compatibility of CBZ with HPMC-AS/HPC-EF, enabling stable ASD formation validated by DSC, PLM, and PXRD. The full factorial design revealed that printing speed was the dominant parameter governing dissolution behavior, with high speeds accelerating release and low speeds prolonging release through porosity-modulated diffusion control. RSM quadratic models showed optimal fits for t_50% (R² = 0.9936) and Q_4h (R² = 0.9019), highlighting the predictability of release kinetics via process parameter tuning. This work demonstrates the adaptability of polymer composite AM for tailoring drug release profiles, balancing mechanical integrity, release kinetics, and manufacturing scalability to advance multifunctional 3D-printed drug delivery devices in pharmaceutics. Full article

Pharmaceuticals are increasingly being detected in coastal ecosystems globally, but contamination and bioaccumulation levels are understudied in temporarily closed estuaries. In these systems, limited freshwater inputs and periodic closure may predispose them to pharmaceutical accumulation. We quantified in situ water column pharmaceutical levels at five sites in a temporarily closed model urban estuary (Zandvlei Estuary) in Cape Town, South Africa, that has been heavily anthropogenically modified. The results indicate an almost 100-fold greater concentration of pharmaceuticals in the estuary relative to False Bay, into which the estuary discharges, with acetaminophen (max: 2.531 µg/L) and sulfamethoxazole (max: 0.138 µg/L) being the primary pollutants. Acetaminophen was potentially bioaccumulative, while nevirapine, carbamazepine and sulfamethoxazole were bioaccumulated (BAF > 5000 L/kg) by sandprawns (Kraussillichirus kraussi), which are key coastal endobenthic ecosystem engineers in southern Africa. The assimilative capacity of temporarily closed estuarine environments may be adversely impacted by wastewater discharges that contain diverse pharmaceuticals, based upon the high bioaccumulation detected in key benthic engineers. Full article

The pharmaceutical industry faces significant challenges when promising drug candidates fail during development due to suboptimal ADME (absorption, distribution, metabolism, excretion) properties or toxicity concerns. Natural compounds are subject to the same pharmacokinetic considerations. In silico approaches offer a compelling advantage—they eliminate the need for physical samples and laboratory facilities, while providing rapid and cost-effective alternatives to expensive and time-consuming experimental testing. Computational methods can often effectively address common challenges associated with natural compounds, such as chemical instability and poor solubility. Through a review of the relevant scientific literature, we present a comprehensive analysis of in silico methods and tools used for ADME prediction, specifically examining their application to natural compounds. Whereas we focus on identifying the predominant computational approaches applicable to natural compounds, these tools were developed for conventional drug discovery and are of general use. We examine an array of computational approaches for evaluating natural compounds, including fundamental methods like quantum mechanics calculations, molecular docking, and pharmacophore modeling, as well as more complex techniques such as QSAR analysis, molecular dynamics simulations, and PBPK modeling. Full article

Background: The quality of decision-making processes is increasingly recognized as critical to public trust and policy sustainability. Objectives: This narrative review aims to identify and describe process-focused decision support models (DSMs) applied in pharmaceutical policy, and to examine their potential contributions to improving procedural quality in decisions related to pricing, reimbursement, and access to medicines. Methods: Relevant peer-reviewed and gray literature published between 2000 and 2025 was considered, drawing from key databases (e.g., PubMed and Scopus) and international policy reports (e.g., WHO, ISPOR, and HTA agencies). Studies were included if they provided insights into DSMs addressing at least one dimension of decision process quality. Results: Findings are synthesized narratively and organized by tool type, application context, and key quality dimensions. Frequently referenced tools included the Quality of Decision-Making Orientation Scheme (QoDoS), WHO-INTEGRATE, and AGREE II. QoDoS emerged as the only tool applied across regulatory, HTA, and industry settings, evaluating both individual- and organizational-level practices. WHO-INTEGRATE highlighted equity and legitimacy considerations but lacked a structured format. Overall, most tools demonstrated benefits in promoting internal consistency, transparency, and stakeholder engagement; however, their adoption remains limited, especially in low- and middle-income countries. Conclusions: Process-focused DSMs offer promising avenues for enhancing transparency, consistency, and legitimacy in pharmaceutical policy. Further exploration is needed to standardize evaluation approaches and expand the use of DSMs in diverse health systems. Full article

Medicinal plants and animal-derived proteins represent valuable natural sources of bioactive components with pharmaceutical potential. Whilst some medicinal plants and animal-derived proteins also offer rich sources of anticoagulant bioactive peptides, their development faces multiple challenges: anticoagulant evaluation relies on single-parameter assays with limited reliability, native proteins demonstrate suboptimal activity without enzymatic treatment, and few researchers investigate bioavailable peptides. Our study establishes an innovative framework using the leech as a case study to overcome these barriers. A novel anticoagulant evaluation model was first established with the Critic-G1 weighting method. And we optimized the enzymatically hydrolyzed extracts with high activity using Box–Behnken response surface methodology. Subsequently, the everted gut sac model was implemented to simulate intestinal absorption and screen for absorbable peptide fractions. Furthermore, peptidomics was employed to identify the bioactive peptides. Lastly, we identified the bioactivity using anticoagulation assays. Results indicated that the optimal hydrolysis conditions were achieved with trypsin at 50.48 °C, an enzyme-to-substrate ratio of 6.78%, 7.51 h, and pH of 8.06. The peptide DLRWM was identified through integrated peptidomics and molecular docking approaches, with subsequent activity validation demonstrating its potent anticoagulant effects. This study has successfully identified a novel anticoagulant peptide (DLRWM) with confirmed intestinal absorption properties and provides a template for unlocking the pharmaceutical potential of medicinal animal proteins. Full article

Lactic acid (LA) is a high-value chemical with growing demand for the production of polymers and plastics and in the food and pharmaceutical industries. However, production costs remain a significant constraint when using conventional food-grade substrates. This study investigates Ivorian sugarcane molasses, an abundant agro-industrial by-product, as a low-cost carbon source for LA production via batch fermentation with Limosilactobacillus fermentum ATCC 9338. Molasses was pretreated by acid hydrolysis to improve fermentability, increasing glucose and fructose concentrations. Comparative fermentations using raw and pretreated molasses showed a 75% increase in LA production (32.4 ± 0.03 g/L) after pretreatment. Optimisation using Box–Behnken design revealed that the initial sugar concentration, inoculation rate, and stirring speed significantly influenced lactic acid production. Under optimal conditions, a maximum LA concentration of 52.4 ± 0.49 g/L was achieved with a yield of 0.95 g/g and productivity of 0.73 g/L·h. Kinetic analysis confirmed efficient sugar utilisation under the optimised conditions, and polarimetry revealed a near-racemic lactic acid. A simplified cost analysis showed that molasses could reduce carbon source costs by over 70% compared to refined sugars, supporting its economic viability. This work demonstrates the potential of pretreated molasses under robust fermentation conditions as a sustainable and cost-effective substrate for LA production in resource-limited contexts. The approach aligns with circular bioeconomy principles and presents a replicable model for decentralised bioproduction in a developing country like Côte d’Ivoire. Full article

Fibrate pharmaceuticals (fibrates), as a widespread class of emerging contaminants, pose potential risks to both ecological systems and human health. The photocatalytic system based on nitrogen (N) and fluorine (F) co-doped TiO₂ nanotube arrays (NF-TNAs) provides a renewable solution for fibrate pharmaceutical removal from water, powered by inexhaustible sunlight. In this study, the degradation of two typical fibrates, i.e., bezafibrate (BZF) and ciprofibrate (CPF), under simulated sunlight irradiation through NF-TNAs were investigated. The photocatalytic degradation of BZF/CPF was achieved through combined radical and non-radical oxidation processes, while the generation and reaction mechanisms of associated reactive oxygen species (ROS) were examined. Electron paramagnetic resonance detection and quenching tests confirmed the existence of h⁺, •OH, O₂^•−, and ¹O₂, with O₂^•− playing the predominant role. The transformation products (TPs) of BZF/CPF were identified through high-resolution mass spectrometry analysis combined with quantum chemical calculations to elucidate the degradation pathways. The influence of co-existing ions and typical natural organic matters (NOM) on BZF/CPF degradation were also tested. Eventually, the ecological risk of BZF/CPF transformation products was assessed through quantitative structure–activity relationship (QSAR) modeling, and the results showed that the proposed photocatalytic system can largely alleviate fibrate toxicity. Full article

The integration of computational intelligence techniques into pharmaceutical wastewater treatment offers promising opportunities to improve process efficiency and minimize operational costs. This study compares the predictive capabilities of Response Surface Methodology (RSM) and Artificial Neural Network (ANN) models in forecasting the rejection efficiencies of caffeine and paracetamol using AFC 40 and AFC 80 nanofiltration (NF) membranes. Experiments were conducted under varying operating conditions, including transmembrane pressure, feed concentration, and flow rate. The predictive performance of both models was evaluated using statistical metrics such as the Coefficient of Determination (R²), Root Mean Square Error (RMSE), Marquardt’s Percentage Squared Error Deviation (MPSED), Hybrid fractional error function (HYBRID), and Average Absolute Deviation (AAD). Both models demonstrated strong predictive accuracy, with R² values of 0.9867 and 0.9832 for RSM and ANN, respectively, in AFC 40 membranes, and 0.9769 and 0.9922 in AFC 80 membranes. While both approaches closely matched the experimental results, the ANN model consistently yielded lower error values and higher R² values, indicating superior predictive performance. These findings support the application of ANNs as a robust modelling tool in optimizing NF membrane processes for pharmaceutical removal. Full article

Introduction: The gut microbiota is vital for human health, and its modulation through dietary and pharmaceutical compounds has gained increasing attention. Among gut microbes, Akkermansia muciniphila has been extensively researched due to its role in maintaining intestinal barrier integrity, regulating energy metabolism, and influencing inflammatory responses. Subject: To analyze and synthesize the available scientific evidence on the influence of various bioactive compounds, including prebiotics, polyphenols, antioxidants, and pharmaceutical agents, on the abundance and activity of A. muciniphila, considering underlying mechanisms, microbial context, and its therapeutic potential for improving metabolic and intestinal health. Methods: A systematic literature review was conducted in accordance with the PRISMA 2020 guidelines. Databases such as PubMed, ScienceDirect, Scopus, Web of Science, SciFinder-n, and Google Scholar were searched for publications from 2004 to 2025. Experimental studies in animal models or humans that evaluated the impact of bioactive compounds on the abundance or activity of A. muciniphila were prioritized. The selection process was managed using the Covidence platform. Results: A total of 78 studies were included in the qualitative synthesis. This review compiles and analyzes experimental evidence on the interaction between A. muciniphila and various bioactive compounds, including prebiotics, antioxidants, flavonoids, and selected pharmaceutical agents. Factors such as the chemical structure of the compounds, microbial environment, underlying mechanisms, production of short-chain fatty acids (SCFAs), and mucin interactions were considered. Compounds such as resistant starch type 2, GOS, 2′-fucosyllactose, quercetin, resveratrol, metformin, and dapagliflozin showed beneficial effects on A. muciniphila through direct or indirect pathways. Discussion: Variability across studies reflects the influence of multiple variables, including compound type, dose, intervention duration, experimental models, and analytical methods. These differences emphasize the need for a contextualized approach when designing microbiota-based interventions. Conclusions: A. muciniphila emerges as a promising therapeutic target for managing metabolic and inflammatory diseases. Further mechanistic and clinical studies are necessary to validate its role and to support the development of personalized microbiota-based treatment interventions. Full article

(1) Background: The urate-lowering effects of three iridoid glycosides, which are paederosidic acid, paederosidic acid methyl ester, and paederoside, isolated from Paederia foetida and the protection they provide against hyperuricemia-induced kidney injury were investigated in a rat model. (2) Methods: A hyperuricemia (HUA) rat model was established in Sprague-Dawley (SD) rats through intraperitoneal potassium oxonate (PO) and intragastrical adenine for 2 weeks. Subsequently, rats in the pharmaceutical intervention groups received corresponding drug treatments at a concentration of 40 mg/kg/day, maintained consistently for 7 days. (3) Results: The results showed that three compounds reduced serum urate (SU), creatinine (CRE), and blood urea nitrogen (BUN) levels and that the urinary excretion levels of uric acid, urine urea nitrogen, and creatinine increased. Furthermore, the administration of three iridoid glycosides enhanced renal filtration capacity, as demonstrated by the elevated 24 h creatinine clearance rate (CCR) and 24 h uric acid clearance rate (CUA); improved the fraction excretion of uric acid (FEUA); and attenuated renal damage. Finally, three iridoid glycosides promoted uric acid excretion in HUA rats by downregulating URAT1 and GLUT9 and upregulating ABCG2, OAT1, and OAT3. Moreover, the molecular docking results further corroborated the finding that the three compounds can bind to multiple sites of the uric acid transporter via hydrogen, P-π, and hydrophobic bonds. (4) Conclusions: The three iridoid glycosides were found to lower SU levels by increasing uric acid excretion. They are promising natural products for the prevention of HUA and HUA-induced kidney injury. Full article

Coronary artery disease (CAD) constitutes a major contributor to morbidity, mortality and healthcare burden worldwide. Recent innovations in imaging modalities, pharmaceuticals and interventional techniques have revolutionized diagnostic and treatment options, necessitating the reevaluation of established drug protocols or the consideration of newer alternatives. The utilization of beta blockers (BBs) in the setting of acute myocardial infarction (AMI), shifting from the pre-reperfusion to the thrombolytic and finally the primary percutaneous coronary intervention (pPCI) era, has become increasingly more selective and contentious. Nonetheless, the extent of myocardial necrosis remains a key predictor of outcomes in this patient population, with large trials establishing the beneficial use of beta blockers. Computed tomography coronary angiography (CTCA) has emerged as a highly effective diagnostic tool for delineating the coronary anatomy and atheromatous plaque characteristics, with the added capability of MESH-3D model generation. Induction and preservation of a low heart rate (HR), regardless of the underlying sequence, is of critical importance for high-quality results. Landiolol is an intravenous beta blocker with an ultra-short duration of action (t1/2 = 4 min) and remarkable β1-receptor specificity (β1/β2 = 255) and pharmacokinetics that support its potential for systematic integration into clinical practice. It has been increasingly recognized for its importance in both acute (primarily studied in STEMI and, to a lesser extent, NSTEMI pPCI) and chronic (mainly studied in elective PCI) CAD settings. Given the limited literature focusing specifically on landiolol, the aim of this narrative review is to examine its pharmacological properties and evaluate its current and future role in enhancing both diagnostic imaging quality and therapeutic outcomes in patients with CAD. Full article

Wounds are undeniably important gateways for pathogens to enter the body. In addition to their detrimental local effects, they can also cause adverse systemic effects. For this reason, developing methods for eradicating pathogens from wounds is a challenging medical issue. Polymers, particularly hydrogels, are one of the more essential materials for designing novel drug-delivery systems, thanks to the ease of tuning their structures. This work exploits this property by utilizing copolymerization, microwave modification, and drug-loading processes to obtain antibacterial gels. Synthesized xylitol-modified glycidyl methacrylate-co-ethyl methacrylate ([P(EMA)-co-(GMA)]-Xyl]) matrices were loaded with bacitracin, gentian violet, furazidine, and brilliant green, used as active pharmaceutical ingredients (APIs). The hydrophilic properties, API release mechanism, and antibacterial properties of the obtained hydrogels against Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus epidermidis containing [P(EMA)-co-(GMA)]-Xyl] were studied. The hydrogels with the APIs efficiently inhibit bacteria growth with low doses of drugs, and our findings are statistically significant, confirmed with ANOVA analysis at p = 0.05. The results confirmed that the proposed system is hydrophilic and has extended the drug-release capabilities of APIs with a controlled burst effect based on [P(EMA)-co-(GMA)]-Xyl] content in the hydrogel. Hydrogels are characterized by the prolonged release of APIs in a very short time (a few minutes). Although the amount of released APIs is about 10%, it still exceeds the minimum inhibitory concentrations of drugs. Several kinetic models (first-order, second-order, Baker–Lonsdale, and Korsmeyer–Peppas) were applied to fit the API release data from the [P(EMA)-co-(GMA)]-Xyl-based hydrogel. The best fit of the Korsmeyer–Peppas kinetic model to the experimental data was determined, and it was confirmed that a diffusion-controlled release mechanism of the APIs from the studied hydrogels is dominant, which is desirable for applications requiring a consistent, controlled release of therapeutic agents. A statistical analysis of API release using Linear Mixed Model was performed, examining the relationship between % mass of API, sample (hydrogels and control), time, sample–time interaction, and variability between individuals. The model fits the data well, as evidenced by the determination coefficients close to 1. The analyzed interactions in the data are reliable and statistically significant (p < 0.001). The outcome of this study suggests that the presented acrylate-based gel is a promising candidate for developing wound dressings. Full article

Traditional Chinese medicine (TCM), a holistic medical system rooted in dialectical theories and natural product-based therapies, has served as a cornerstone of healthcare systems for millennia. While its empirical efficacy is widely recognized, the polypharmacological mechanisms stemming from its multi-component nature remain poorly characterized. The conventional trial-and-error approaches for bioactive compound screening from herbs raise sustainability concerns, including excessive resource consumption and suboptimal temporal efficiency. The integration of artificial intelligence (AI) and multi-omics technologies with network pharmacology (NP) has emerged as a transformative methodology aligned with TCM’s inherent “multi-component, multi-target, multi-pathway” therapeutic characteristics. This convergent review provides a computational framework to decode complex bioactive compound–target–pathway networks through two synergistic strategies, (i) NP-driven dynamics interaction network modeling and (ii) AI-enhanced multi-omics data mining, thereby accelerating drug discovery and reducing experimental costs. Our analysis of 7288 publications systematically maps NP-AI–omics integration workflows for natural product screening. The proposed framework enables sustainable drug discovery through data-driven compound prioritization, systematic repurposing of herbal formulations via mechanism-based validation, and the development of evidence-based novel TCM prescriptions. This paradigm bridges empirical TCM knowledge with mechanism-driven precision medicine, offering a theoretical basis for reconciling traditional medicine with modern pharmaceutical innovation. Full article