Bojungikgitang (BJIGT), Ijintang (IJT), and Cheongsanggyeontongtang (CSGTT) are traditional herbal formulations with a long history of use in East Asian traditional medicine for the symptomatic management of cardiovascular and cerebrovascular diseases. Although these formulations are frequently coadministered with anticoagulants, clinical evidence on their interactions with direct oral anticoagulants (DOAC) remains scarce. This study aimed to evaluate the effects of BJIGT, IJT, and CSGTT on the pharmacokinetics and pharmacodynamics of edoxaban, a widely used DOAC. In a fixed-sequence, two-period clinical study, healthy volunteers received 60 mg edoxaban alone and after repeated dosing with BJIGT, IJT, or CSGTT. Plasma concentrations of edoxaban and its active metabolite M4 were quantified by liquid chromatography coupled with tandem mass spectrometry. Pharmacokinetic parameters were compared using linear mixed-effects models. Pharmacodynamic effects were assessed with prothrombin time and activated partial thromboplastin time. The CYP3A4 inhibitory potential of BJIGT, IJT, and CSGTT was evaluated in vitro. BJIGT significantly increased edoxaban exposure, approximately doubling systemic levels, whereas IJT exerted minimal effects and CSGTT reduced exposure by approximately 40
To overcome the poor aqueous solubility and low oral bioavailability, an amorphous solid dispersion (ASD) system was developed and mechanistically evaluated using various polymeric carriers which stabilized the drug through intermolecular interactions. ASDs of a weakly basic drug, nimodipine were prepared using acidic/non–ionic polymers (HPC, HPMCAS, HPMCP, and PVP K25) via spray−drying and melt−quenching techniques. The solid−state was evaluated using glass transition temperature (Tg) and morphological assessment to optimize the formulation and suppress recrystallization. Predictive miscibility was established using Hansen solubility parameters (δ) and Gordon−Taylor equation. Thermodynamic phase equilibria and molecular interactions were analyzed using the Flory−Huggins parameter ( χ ) and PC−SAFT modeling. Dissolution kinetics were modeled using the Korsmeyer−Peppas equation. Theoretical miscibility was confirmed, as all drug−polymer interactions exhibited Δδ < 7 MPa0.5. Experimental Tgaligned closely with Gordon−Taylor predictions, and χ <0.5 indicated strong, favorable micro−level interactions. PC−SAFT−derived ternary phase diagrams demonstrated that ethanol−based processing broadened the thermodynamic stability window compared to aqueous systems. The optimized spray−dried HPMCP formulation exhibited a superior dissolution profile with a dissolution efficiency (DE) of 0.901 at pH 6.0 achieving rapid supersaturation (85.51
Food intake can substantially alter the pharmacokinetics of orally administered drugs by changing gastrointestinal (GI) pH, motility, gastric emptying, bile secretion, luminal composition, drug solubility, and intestinal absorption. These interactions make the food effect an important determinant of systemic exposure, therapeutic response, and dosing recommendations, yet the mechanisms responsible for fed-fasted differences are often incompletely understood. This structured mechanistic narrative review synthesizes the physiological, physicochemical, metabolic, transporter-mediated, and formulation-related determinants of food effects. Of 1,237 records identified, 241 articles underwent full-text assessment and 74 studies were included in the final mechanistic synthesis. The review evaluates how gastric pH and emptying, bile-mediated micellization, intestinal transporters, drug properties (including pKa, solubility, and logD), meal composition, and formulation design determine the direction and magnitude of food and beverage effects within the Biopharmaceutics Classification System framework. Mechanistic understanding of food-drug interactions supports rational formulation design, more reliable dosing instructions, and improved clinical decision-making. Controlled-release systems, amorphous solid dispersions, nanoparticles, and lipid-based formulations can reduce fed-fasted variability, although their performance must be confirmed under dynamic gastrointestinal conditions. Future research should integrate biorelevant dissolution, precipitation and lymphatic-uptake models, physiologically based pharmacokinetic simulations, and artificial intelligence to predict food effects earlier and more reliably during drug development.
Cancer therapy is frequently limited by poor tumor selectivity, systemic toxicity, unfavorable pharmacokinetics, and therapeutic resistance. Nanocarrier-based drug delivery systems have emerged as promising pharmaceutical platforms for improving therapeutic precision, enhancing tumor accumulation, and enabling personalized cancer treatment strategies. This review discusses major nanocarrier systems employed in precision oncology, including liposomes, polymeric nanoparticles, dendrimers, carbon nanotubes, and quantum dots, with emphasis on their pharmaceutical design, physicochemical properties, and therapeutic relevance. Particular attention is given to tumor-targeting approaches based on enhanced permeability and retention-mediated passive targeting and ligand-mediated active targeting. The review further examines multifunctional and theranostic nanoplatforms integrating imaging and therapy within a single system to support real-time monitoring of therapeutic response. In addition, recent advances in biomarker-guided therapy, stimuli-responsive drug delivery, combination therapeutics, and clinically translated nanoformulations are discussed alongside current challenges associated with biodistribution variability, large-scale manufacturing, long-term safety, and regulatory complexity. Nanocarrier-based drug delivery systems continue to demonstrate substantial potential for advancing precision oncology by improving drug delivery efficiency, therapeutic selectivity, and patient-tailored treatment outcomes. Future progress in pharmaceutical engineering, scalable manufacturing, biomarker-driven stratification, and clinically translatable multifunctional nanoplatforms may further accelerate the integration of nanomedicine into routine cancer management and personalized therapeutic interventions.
Oral delivery remains the predominant route of drug administration due to its convenience and patient acceptability; however, many new chemical entities exhibit poor aqueous solubility and limited permeability, resulting in sub-optimal bioavailability. These challenges are particularly relevant for BCS class II–IV compounds. This review examines the multifunctional roles of lipid-based excipients in oral dosage forms, with emphasis on their pharmaceutical contributions as described within Gattefossé’s lipid portfolio. Lipid excipients are discussed as functional materials that enhance oral bioavailability through mechanisms including self-emulsification, sustained release, enhanced intestinal permeability, P-glycoprotein inhibition, and promotion of lymphatic transport. Additional roles such as taste masking, protection of labile actives, and lubrication during tableting are addressed. Representative nonionic surfactant systems including Gelucire®, Labrasol®, Compritol®, and Precirol® are highlighted in the context of formulation considerations. The multifunctionality of lipid excipients positions them as key enabling components for addressing solubility and permeability limitations in oral drug delivery. Their ability to improve both biopharmaceutical performance and manufacturing characteristics supports their continued integration into formulation design strategies.
Cannabidiol (CBD) exhibits potent antioxidant, anti-inflammatory, and neuroprotective properties; however, its therapeutic application in Alzheimer’s disease (AD) is limited by poor aqueous solubility, instability, and restricted brain delivery. This study aimed to develop a nanoparticle-based delivery system to enhance CBD bioavailability and brain-associated therapeutic efficacy. CBD-loaded human serum albumin nanoparticles (CBD-HSA-NPs) were prepared using a modified self-assembly technique. The physicochemical properties, encapsulation efficiency, and in vitro release behavior were characterized. Anti-amyloidogenic activity, reactive oxygen species (ROS) inhibition, and neuroprotective effects were evaluated in vitro. Cellular uptake was assessed in hCMEC/d3 cells using Cy5.5-loaded nanoparticles. In vivo therapeutic efficacy was investigated in an Aβ₁–₄₂-induced AD mouse model through behavioral, biochemical, and histological analyses. The optimized CBD-HSA-NPs exhibited a mean particle size of 197.2 ± 1.1 nm, a polydispersity index of 0.283, and a zeta potential of − 27.8 ± 0.8 mV, with high encapsulation efficiency (87.4 ± 3.9
Peptide drugs occupy an intermediate position between small-molecule drugs and biologics in terms of molecular size and structural complexity. Owing to their unique characteristics, they face regulatory challenges for quality assessment and control, as existing regulatory frameworks for small molecules and biologics are not fully applicable to peptide drugs. To address these challenges, regulatory agencies and pharmacopeial authorities have developed guidelines and analytical standards based on scientific considerations to ensure manufacturing consistency and reliable quality evaluation. This review examines recent regulatory trends for peptide drugs by analyzing guidelines and standards issued by major regulatory agencies and pharmacopoeias, focusing on analytical strategies for identification, impurity testing, and assay. The inherent complexity of peptides requires comprehensive and orthogonal analytical approaches to accurately characterize their structural attributes and satisfy stringent regulatory requirements. In this context, advanced analytical techniques such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy play complementary roles in peptide quality assessment. MS is a highly sensitive tool for sequence analysis and impurity profiling, while NMR offers unique capabilities for structural elucidation, higher-order structural assessment, and orthogonal confirmation. Recent advances in analytical technologies have contributed significantly to the development of science-based regulatory strategies for synthetic peptide drugs. The continued harmonization of peptide drug regulations, together with the integration of advanced analytical methodologies and industrial perspectives, is expected to facilitate efficient quality assessment and support the production of safe and effective peptide therapeutics.
Isolated hepatocytes (IH) are standard in vitro models for evaluating hepatic metabolism and uptake. This study characterized time-dependent changes in selected metabolic and uptake activities of IH during incubation, and assessed hypothermic preservation at 4 °C as a short-term storage strategy. IH were isolated from rats, and their functional stability was assessed during incubation at 37 °C and preservation at 4 °C. Metabolic activity was measured by the clearance of testosterone, 4-methylumbelliferone, and buspirone. Uptake activity was evaluated by measuring the hepatic uptake of Zombie Violet and rosuvastatin. Functional stability was quantified using the 90
To overcome the strong inter-particulate interactions between the drug and carrier in dry powder inhalers (DPIs), an amorphous lactose solid dispersion (ALSD) was developed by co-spray drying lactose with magnesium stearate (MgSt) as a novel carrier for fluticasone propionate (FP). To investigate the effects of carrier size, morphology, surface properties, and blending time on aerodynamic performance, the ALSD was compared with commercial references: rough-surfaced spherical lactose (SuperTab® SD11), tomahawk-shaped lactose (Lactohale® 200), and spherical spray-dried lactose, both with and without MgSt. A design of experiments (DoE) approach was employed to optimize the MgSt concentration and blending time. Based on the DoE results, the optimal MgSt amount was established at 0.2
As the prevalence of metabolic dysfunction-associated steatohepatitis (MASH) continues to rise, drug development has accelerated, with growing interest in therapeutic strategies that harness metabolic hormones. Metabolic hormone-based approaches, particularly those originally developed for obesity and diabetes, have shown potential to mitigate MASH. Notably, the glucagon-like peptide-1 receptor (GLP-1R) agonist semaglutide received accelerated approval for MASH in 2025. In addition, GLP-1R-based multi-agonists and candidates leveraging the metabolic actions of fibroblast growth factor (FGF) 21 are in active clinical development for liver disease. This review provides an overview of metabolic hormone-based therapies, including incretin-based drugs and FGF analogs, that are currently under clinical development for MASH. It also discusses liver-targeting strategies to achieve selective hepatic delivery, which may vary according to the expression of liver-specific receptors and fibrosis degree. Within the MASH therapeutic landscape, incretin-based therapies are evolving from GLP-1R mono-agonist to multi-agonist approaches that aim to combine weight loss-mediated benefits with mechanisms that directly modulate hepatic lipid handling and inflammation. Moreover, the therapeutic actions of metabolic hormones in MASH, together with the expression profiles of their corresponding receptors, play a critical role in determining targeting strategies. Stage-specific and liver-selective delivery strategies will likely distinguish next-generation candidates. This review summarizes the pharmacological mechanisms and delivery strategies of each agent class and further explores these receptors as potential targets to inform the development of precision therapeutic approaches.
Fenofibrate (FN), a Biopharmaceutics Classification System (BCS) class II drug, has poor aqueous solubility and low oral bioavailability. This study aimed to develop polyethylene glycol (PEG)-ylated FN-loaded solid lipid nanoparticles (FN-P-SLNs) to enhance oral bioavailability and lipid-lowering efficacy. FN-P-SLNs were prepared at an optimized ratio of FN/lipid/surfactant/PEG/cryoprotectant (0.5:1.36:1.36:0.07:6.7). Particle size, polydispersity index (PDI), and zeta potential were measured. Physicochemical characteristics were analyzed using FT-IR, DSC, XRD, and SEM. Cytotoxicity was evaluated in Caco-2 cells. In vitro drug release was assessed at different pH conditions. Pharmacokinetic parameters (AUCt, Cmax) were compared with raw FN and non-PEGylated FN-SLNs in vivo. Pharmacodynamic effects were evaluated by measuring plasma triglyceride levels in rats. FN-P-SLNs showed a mean particle size of 461 ± 240 nm, PDI 0.35 ± 0.15, and zeta potential −50.7 ± 4.5 mV. FT-IR and DSC confirmed successful encapsulation, and XRD indicated a predominantly amorphous state. SEM revealed spherical to oval nanoparticles. Cell viability exceeded 80
Apigenin (API), a bioactive plant-derived flavonoid, is a potent antiarthritic and anti-inflammatory agent. However, its translational potential is hindered by its extremely low aqueous solubility and poor bioavailability. This study aimed to prepare apigenin-β-cyclodextrin (API-βCD)-loaded liposomes (API-βCD-L) coated with hyaluronic acid (HA) for improved therapeutic activity. The thin-film hydration method was used to prepare API-βCD-L. The formulation was statistically optimized using the Design-Expert Box–Behnken design and subsequently coated with HA. Dynamic light scattering, powder X-ray diffraction, and transmission electron microscopy were used for physicochemical characterization, followed by release behavior and pharmacokinetic (PK) evaluation. Complete Freund’s adjuvant (CFA)-induced arthritis model was used to investigate the antiarthritic efficacy. The optimized API-βCD-L demonstrated a mean particle size (PS) of 198.3 ± 1.83 nm, zeta potential of 29.26 ± 2.5 mV, and
Pharmaceutical nanoparticle involves complex and highly nonlinear interactions between formulation variables and process parameters that are difficult to describe using conventional statistical models. Artificial intelligence (AI) offers an advanced approach to overcoming these limitations and enhancing formulation optimization and quality control. This study aimed to develop an AI-driven framework integrating hybrid machine learning (HML) and a reinforcement learning–enhanced genetic algorithm (GA-RL) to optimize resveratrol-loaded polymeric nanoparticles (RES-PNPs) for cancer treatment. A dataset of RES-PNPs was used to train ML, including linear regression, k-nearest neighbors, support vector machines, and artificial neural networks. HML was constructed to predict particle size (PS), polydispersity index (PDI), zeta potential (ZP), and percentage encapsulation efficiency (
Hypertrophic scarring and atopic dermatitis (AD) are clinically distinct skin disorders that share common pathological mechanisms involving excessive fibrosis, chronic inflammation, immune dysregulation, and oxidative stress associated with dysregulated wound healing. Persistent fibroblast activation, aberrant extracellular matrix remodeling, and impaired epidermal barrier function contribute to pathological tissue regeneration in both conditions. Recent advances in nanotechnology have enabled nanotherapeutic platforms that precisely modulate the cutaneous microenvironment through enhanced skin penetration and localized retention. This review categorizes emerging nanotherapeutic strategies including anti-fibrotic, anti-inflammatory, immunomodulatory, and barrier-restorative approaches. Specific cases such as transforming growth factor-beta (TGF-β) small interfering RNA (siRNA) delivery, reactive oxygen species (ROS) scavenging nanozymes, and lipid-replenishing nanoparticles are discussed in the context of coordinated regulation. By overcoming the limitations of conventional topical treatments, these smart nanosystems offer synergistic therapeutic effects. The future of cutaneous nanotherapy lies in the convergence of scar and AD management through integrated regenerative-immunological strategies. Personalized nanomedicine and bioinspired materials will transition from simple drug delivery to active microenvironmental reprogramming. Addressing long-term safety and lesion-specific targeting efficiency remains a prerequisite for clinical adoption.
This study evaluated the therapeutic benefits of combination therapy with irbesartan (an angiotensin II receptor blocker) and perindopril (an angiotensin-converting enzyme inhibitor) in experimental models of hypertension and cardiovascular injury. Antihypertensive efficacy was assessed in spontaneously hypertensive rats (SHRs) by continuous telemetry monitoring of systolic blood pressure (SBP), mean arterial pressure (MAP), and heart rate (HR). To evaluate cardiovascular protection, myocardial ischemia/reperfusion (MI/R) was induced in SHRs by coronary artery ligation, and neointimal hyperplasia was induced in C57BL/6 mice by femoral artery cuff placement. Protective effects of the drug combination were quantified in each injury model. Co-administration of low doses of both drugs (one-quarter of each high dose) produced BP lowering comparable to that achieved with high-dose monotherapy, without affecting HR. In the MI/R model, high-dose perindopril alone and high-dose combination therapy significantly reduced the infarct zone-to-area at risk (IZ/AAR) ratio in the left ventricle, and increased endothelial nitric oxide synthase (eNOS) expression in occluded vascular tissue. In the cuff-induced vascular injury model, high-dose irbesartan or perindopril reduced neointimal thickness and the BrdU index, and high-dose combination therapy significantly reduced the BrdU index. Perindopril alone and combination therapy also reduced the BrdU index in the medial layer. These findings suggest that combined irbesartan and perindopril therapy may be an effective strategy for treating hypertension and reducing associated cardiovascular complications.
The shift toward continuous health management has increased the need for minimally invasive diagnostics. Dermal interstitial fluid (ISF) is an attractive alternative to blood because its biomarker profile is similar, and it does not coagulate. However, conventional ISF collection remains invasive and inefficient. Microneedle (MN) technology addresses these limitations by painlessly penetrating the stratum corneum, enabling patient-friendly point-of-care testing and self-monitoring. This systematic review examines the physiological characteristics of ISF and the limitations of traditional extraction methods. It analyzes various MN materials (e.g., HA, PLGA, PVA) and structural designs, including solid, hollow, and hydrogel-forming MNs, optimized for efficient fluid sampling. It also describes the integration of MNs with advanced sensing modalities, focusing on mechanisms and recent trends in electrochemical, fluorescence, and immunodiagnostic sensor systems. Despite their potential, MN-integrated sensors face hurdles such as limited extraction volumes, material stability, and the physiological lag time between blood and ISF. Future research must focus on enhancing biomarker specificity and ensuring long-term sensing reliability. Overcoming these challenges will be essential for transitioning from laboratory prototypes to clinical-grade wearable devices that enable real-time, personalized health monitoring.
Nanomedicines such as PEGylated liposomal doxorubicin are non-biological complex drugs whose quality and therapeutic performance are governed by intricate nanoparticle characteristics. Regulatory agencies worldwide consistently emphasize comprehensive physicochemical characterization as a prerequisite for assuring quality, safety, and efficacy of complex generic products. This study aimed to establish a regulatory-aligned critical quality attribute (CQA) framework for nanomedicines by integrating guidance from U.S., European, Japanese, and Korean regulatory authorities. PEGylated liposomal doxorubicin was selected as a representative case study. Regulatory guidance documents from multiple agencies were systematically reviewed to identify nanoparticle attributes critical to product performance. The reference listed drug, Doxil® (marketed as Caelyx® in Europe and Korea), was comprehensively characterized under varying dispersion media, pH, ionic strength, and temperature conditions using standardized and reproducible analytical methods to assess structural and functional attributes of the liposomal carrier. Cross-agency regulatory perspectives converged on a set of CQAs encompassing size-related properties, surface characteristics, drug encapsulation, and stability-related parameters. Experimental characterization demonstrated that these attributes were sensitive to environmental conditions and directly reflected the structural integrity and functional performance of the liposomal formulation. This study proposes a scientifically grounded CQA reference framework that links nanoparticle structure to performance while aligning with multi-agency regulatory expectations. The framework provides a transferable analytical approach to support the development, evaluation, and regulatory assessment of complex generic nanomedicines.
Perfluorocarbon (PFC)-based nanoemulsions (NEs) have been extensively investigated as artificial blood substitutes because of their high oxygen solubility. However, their clinical translation has been significantly hindered by poor stability during storage and administration. We reinterpreted the instability of PFC NEs from a bulk rheological perspective and established an effective additive-based stabilization strategy. Different plasma volume expanders (PVEs) were systematically evaluated as thickening additives for PFC NEs. Long-term changes in particle size, polydispersity index, phase separation, and sedimentation behavior were analyzed, and formulation stability was quantitatively assessed using the Turbiscan analysis. Physicochemical properties relevant to intravenous administration, including osmotic pressure, viscosity, and pH, were characterized for obtaining optimized formulations. Both in vitro and in vivo safety evaluations were conducted to assess biocompatibility. Most conventional polymer-based thickeners failed to sufficiently improve the stability of PFC NEs or induce aggregation and phase separation. In contrast, the specific PVE effectively suppressed sedimentation and phase separation under long-term storage conditions. The optimized formulation maintained particle stability while exhibiting physicochemical properties comparable to those of an intravenous injection. No significant cytotoxicity or in vivo toxicity was observed in cellular or animal models. The instability of PFC NEs is governed by bulk rheological properties rather than interfacial instability alone, and presents a clinically relevant stabilization strategy using PVEs. This approach provides a practical method for enhancing the clinical feasibility of PFC-based artificial blood formulations.
Accurate prediction of human pharmacokinetics (PK) remains a critical challenge in drug development. Conventional animal-based approaches face inherent limitations due to species differences, driving progress toward more accurate and human-relevant predictive methodologies. This review discusses the evolution of human PK prediction methodologies from conventional approaches to emerging technologies. Traditional methods, including allometric scaling, in vitro–in vivo extrapolation, and physiologically based pharmacokinetic modeling, are first examined, with emphasis on their principles, applications, and limitations through representative case studies. Subsequently, emerging approaches, such as artificial intelligence (AI) and machine learning applications, organ-on-a-chip systems, and other advanced in vitro models, are explored. A comprehensive comparison between conventional and AI-based approaches is provided, addressing data requirements, modeling complexity, predictive performance, and practical applicability. Current implementation challenges—including the need for standardization, barriers to cross-method integration, and regulatory considerations—are also discussed. The future of human PK prediction depends on the strategic integration of complementary methodologies. Conventional methods provide mechanistic transparency, AI-driven approaches offer screening efficiency, and advanced in vitro models deliver physiological relevance. Achieving this integration requires standardized validation frameworks and clear regulatory guidance to support multi-method applications.
This study aims to assess the applicability of flow-imaging microscopy (FI) using morphology-derived parameters to the label-free quantitative analysis of natural killer (NK) cells. Serially diluted NK − cells were analyzed in triplicate using FI, an automated cell counter, and fluorescence-activated cell sorting. A morphology-assisted software filter was developed and optimized in FI based on reference parameters obtained from CC and FACS, which included cell size, circularity, aspect ratio, and intensity profile. The FI method achieved excellent linearity (R² = 0.9996), accuracy of (98 − 102)
