International Journal of Pharmaceutics最新文献

Optimizing pulmonary drug delivery requires a detailed understanding of aerosol-mucus interactions, particularly under pathological conditions such as chronic obstructive pulmonary disease (COPD), where mucus composition, rheology, and surface properties are markedly altered. This study investigated how modulating the drug-mucus contact angle-a surrogate for mucosal wettability-affects deposition outcomes in pressurized metered-dose inhalers (pMDIs). A realistic mouth-throat (MT) model was fabricated and coated with artificial pulmonary mucus, then experimentally characterized to establish a baseline contact angle of 22.5°. This baseline value was implemented in the numerical model, which was validated against in vitro Next Generation Impactor (NGI) data and subsequently extended to simulate contact angles of 40° and 60°, representing reduced wettability scenarios typical of severe COPD. Our findings showed that disease-altered wettability conditions (θ = 60°) increased overall drug deposition by approximately 13.4 % compared with the healthy airway condition (θ = 22.5°), underscoring the adhesive contribution to droplet retention. Simulations further revealed that oropharyngeal deposition is highly sensitive to mucus wettability: lower interfacial tension promoted complete spreading and mucosal absorption, whereas higher interfacial tension led to droplet rebound, limited transfer, and downstream re-entrainment. Collectively, these findings provide mechanistic insight into how controlling drug-mucus interfacial characteristics can improve aerosol delivery in disease-compromised airways.

Continuous manufacturing technologies such as twin-screw wet granulation (TSWG) offer advantages over batch processing but face challenges when producing low-dose formulations. This study evaluated the impact of API/binder addition methods and granulator settings on critical granule quality attributes. Two low-dose model formulations were investigated, containing either a highly water-soluble (metformin.HCl) or a practically water-insoluble (celecoxib) Active Pharmaceutical Ingredient (API). A full factorial screening design was conducted by varying the liquid-to-solid (L/S) ratio, screw speed, screw design, and API/binder addition method. L/S ratio and screw speed exhibited the strongest effect on granule size, with higher settings reducing fines and narrowing the size distribution. Across all evaluated conditions, an inhomogeneous API distribution over granule size fractions was observed, with fines consistently underdosed and larger granules overdosed. Compartmental analysis revealed that the inhomogeneity originated in the wetting zone, while the first kneading zone most significantly improved uniformity. API wettability impacted nucleation behavior, with metformin.HCl incorporated in over-wetted nuclei and celecoxib forming surface layers around excipient cores. To quantify API uniformity, the weighted mean absolute deviation (WMAD), a novel metric, was introduced. The lowest WMAD values were obtained at high L/S ratio and screw speed, while API/binder addition method had a minimal impact.

Establishing robust processing windows for pharmaceutical polymers during hot-melt extrusion (HME) remains challenging, as conventional thermal analyses reveal little about early chemical change. Here, selected-ion-flow-tube-mass-spectrometry (SIFT-MS) combined with principal component analysis (PCA) was used to characterise real-time volatile evolution under both thermogravimetric (TGA) and extrusion conditions. Centroid-distance mapping and PCA loadings revealed distinct transitions, providing a data-driven means of defining the onset of significant chemical change. Across four representative polymers (Soluplus®, Affinisol™15LV, Kollidon® VA64, and Plasdone™ S630 Ultra), each exhibited changes in volatile composition that marked the onset of temperature-driven chemical evolution. Soluplus® and Plasdone™ S630 Ultra remained stable up to ≈190 °C with optimum extrusion ranges of 150-170 °C. Kollidon® VA64 showed earlier volatile emergence near 180 °C, defining a 160-180 °C window, while Affinisol™15LV, the most viscous system, degraded above 190-200 °C, narrowing its range to 170-185 °C. A brief rheological assessment supported these chemically defined limits, confirming that changes in volatile composition coincide with softening behaviour. Overall, SIFT-MS detected subtle, low-level volatile changes that emerge well before conventional thermal indicators, enabling rapid, non-destructive definition of polymer-specific extrusion windows and enhancing process understanding in amorphous solid dispersion manufacture. Through this analysis we were able to provide a narrower processing range than those defined by their respective manufacturers.

Protein and antibody therapeutics, distinguished by exceptional activity, specificity, and precise biological functions, are crucial in modern pharmaceuticals. Their clinical success depends on developability, encompassing physicochemical properties to ensure stability and safety and are governed by protein characteristics and formulation composition. However, formulation development of biopharmaceutical drugs remains hindered by inefficient and expensive trial-and-error experiments. In this study, we constructed four developability-related datasets, each containing both protein and excipient information. The datasets cover conformational stability with 986 entries, colloidal stability with 919 entries, viscosity with 900 entries, and solubility with 749 entries, where each data entry represents a single measurement of a specific developability property under certain protein and formulation conditions such as pH, ionic strength, excipient, etc. The multimodal deep learning framework (Formulation_Protein) was designed to capture the complex interplay among three-dimensional structural data, sequence, amino acid composition descriptors, and formulation compositions to enable accurate prediction of four protein formulation developability parameters. This architecture leverages transfer learning in conjunction with conventional machine learning algorithms to enable comprehensive feature representation and prediction. Formulation_Protein demonstrated good performance, obtaining average accuracies of 0.925 for conformational stability, 0.858 for colloidal stability, 0.917 for viscosity, and 0.742 for solubility on the test sets. Further experimental validation was performed on 9 proteins across 65 formulations. In conclusion, this study present Formulation_Protein, a multimodal deep learning framework, for comprehensive developability assessment in early stage to accelerate protein and antibody development.

The antimicrobial potential of the water-based probiotic Symprove® against three clinically relevant pathogens, Clostridium perfringens, Klebsiella pneumoniae and Listeria monocytogenes, was investigated in vitro. Isothermal calorimetry and classical microbiological techniques were used to give an evaluation of Symprove's antimicrobial efficacy and mechanism of action against the pathogens. In mixed culture, the pathogenic species initially exhibited faster growth than the probiotic bacteria in Symprove, but the final bacterial counts revealed a significant reduction in pathogen viability compared with controls. After 48 h of co-incubation, more than a 3-fold log reduction in colony-forming unit (CFU) growth was observed for all three pathogens evaluated, demonstrating a strong inhibitory effect (in particular, levels of C. perfringens and K. pneumoniae declined to zero). The mechanism of inhibition appears largely pH-dependent, driven by production of lactic acid from the probiotic strains. These findings support and expand previous work showing that Symprove exerts antipathogenic effects against common organisms that cause infectious diseases and suggest a potential role for Symprove as an adjuvant therapy in infectious diseases.

Airway mucus presents a significant barrier to inhaled drug delivery, particularly for nanoparticle-based interventions, with this barrier exacerbated in chronic respiratory diseases (CRDs) due to hyperviscous secretions and persistent inflammation. In this study, a dual-functional lipid-polymer hybrid nanoparticle was developed to combine rapid mucolysis with sustained anti-inflammatory activity, and its performance was evaluated using both conventional in vitro assays and a physiologically relevant lung-on-a-chip model. Dipalmitoylphosphatidylcholine (DPPC)-coated PLGA nanoparticles (hydrodynamic diameter 378.1 ± 23.0 nm; 58-61 wt% lipid; ζ ≈ +3 mV) encapsulated N-acetylcysteine (NAC) within the lipid shell for rapid release and all-trans retinoic acid (ATRA) within the core for sustained delivery. NAC exhibited a burst release of 44.2-52.5% within 6 h and significantly reduced the viscosity of cystic fibrosis-mimetic mucus, enabling a 26.5-fold higher penetration across a ∼ 0.6 mm mucus plug compared to NAC-free controls. The formulation was well tolerated by pulmonary epithelial and fibroblast cells and demonstrated high cellular uptake driven by the DPPC coating. To assess efficacy under physiologically relevant airway conditions, a human lung-on-a-chip model incorporating air-liquid interface, flow, and cyclic stretch was employed. In this model, repeated dosing of NAC + ATRA nanoparticles resulted in a 2.6-fold reduction in IL-6 and a 2.3-fold reduction in IL-8 levels compared to diseased controls at 72 h, outperforming NAC-free nanoparticles at early timepoints and maintaining suppression over 9 days. These findings demonstrate the therapeutic promise of dual-functional mucopenetrative nanoparticles and establish the utility of lung disease-on-chip platforms for evaluating inhaled nanotherapeutics under physiologically relevant conditions.

Microneedles (MNs), a novel transdermal drug delivery approach, are known for their convenience, dosing accuracy, and ability to enhance patient compliance. Conventional single layer MNs, however, have a drawback: most of the drug resides in the backing layer, which can't permeate the skin, leading to low drug utilization. Herein, to address the limitations of conventional MNs in drug delivery, we proposed a tip-concentrated dissolving microneedle combined with photothermal nanoparticles. Natural biopolymer compounds chondroitin sulfate and carboxymethyl chitosan serve as the matrix. Via a layered design, the drug is concentrated at the tips, with photothermal nanoparticles distributed along the shaft and in the backing layer. The photothermal effect is harnessed to accelerate drug release and enhance transdermal penetration. Compared to traditional MNs, this novel system, through optimized drug distribution and photothermal response, significantly improves drug utilization and delivery efficiency. It also excels in transdermal performance and adaptability to curved skin surfaces. This research not only overcomes the single loading function limitation of single layer MNs but also offers innovative ideas and technical support for developing precise drug delivery systems.

Development of regulatory science tools to facilitate and accelerate accessibility to complex generic drug products continues to be the focus of significant research activity. The application of confocal Raman spectroscopy to the assessment of cutaneous drug pharmacokinetics is a particular example and has been exploited here to compare two approved topical creams (the reference-listed drug product and a generic) of doxepin hydrochloride with an intentionally non-equivalent, laboratory-made solution of the drug. Experiments involved administration of the formulations to pig skin ex vivo for 6 or 12 h (the uptake phase) followed by 2 and 4 h of clearance to generate Raman-assessed absorption-elimination profiles at nominal depths of 5 μm and 25 μm into the skin. This was achieved, despite overlap between spectral features of the drug with those from the skin, using a background signal removal strategy that also allowed the two functional excipients of the laboratory-made solution to be independently tracked. The areas under the Raman signal versus time absorption-elimination profiles showed (as expected) that the two creams were very similar but that the laboratory-made solution was distinctly different. First-order elimination rate constants describing the clearance phase post-application of doxepin from the superficial skin layers into the deeper tissue were also derived from the spectral data. While the experimental design was insufficiently powered to assess bioequivalence, the data background signal separation paradigm notably expands the potential value of the approach to a broader range of chemical species than had been originally envisaged.

Polymeric microparticles have been widely used as carriers for encapsulating and delivering drugs into different regions under the skin, finding applications in management of skin diseases. Although needle-based injections have been extensively explored for microparticle delivery, they are associated with limitations such as pain, risk of infection, and formulation challenges. Alternative, patient-friendly transdermal delivery methods are therefore of significant interest. In this study, we evaluated the feasibility of using a needle-free injection system (Biojector® 2000) to deliver polystyrene microparticle suspensions into agarose hydrogel as a skin-mimicking substrate. We systematically investigated the effects of particle size, concentration, gel stiffness, and standoff distance on penetration dynamics and particle dispersion. We demonstrated that the injector successfully delivered particles up to 50 µm, with smaller particles producing denser dispersions, and higher particle concentrations (0.05% w/v) enhancing kinetic energy retention and full-penetration events. Gel stiffness had the most pronounced effect: stiffer gels slowed penetration, reduced initial jet tip velocity, and constrained particle trajectories, whereas softer gels allowed for faster penetration and wider dispersion. Variation in standoff distance had minimal impact on penetration or dispersion profiles. These findings can inform future efforts to optimise needle-free microparticle delivery in animal or human skin models, supporting the advancement of microparticle-based drug delivery toward clinical application.

Current strategies for treating sensorineural hearing loss include auditory rehabilitation, cochlear implantation, and systemic or local drug administration. Transtympanic injection (TTI) allows local drug delivery to the middle ear, but drug diffusion through the round window membrane (RWM) into the inner ear (IE) remains inconsistent. Microbubble-assisted ultrasound (MB-assisted US) has emerged as promising modality to enhanced RWM permeability. While feasibility and safety have been demonstrated in small animal models, translational validation in large mammals is necessary. This study aimed to compare gadolinium (Gd) diffusion into the IE following MB-assisted US versus passive diffusion in a sheep model, and to assess safety. Five normal-hearing ewes underwent bilateral mastoidectomy. One ear received Gd (Gadovist®) and Vevo MicroMarker® MBs (2.10⁷ MB/mL), followed by MB-assisted US exposure using a 1 MHz US probe (100-μs inter-pulse period, with 300-kPa peak negative pressure for 3-min exposure time). The contralateral ear received Gd via TTI. IE Gd diffusion was assessed by a serial MRI at 10, 20, 30 min and 7 days after Gd delivery. Auditory brainstem responses and vestibular function were evaluated at 1 h pre-treatment and at 7 days post-treatment; metabolomic analysis was performed on perilymph samples. Gd diffusion was greater with MB-assisted US than with TTI, with a 10- and 3.6-fold greater residual volume at 30 min and at Day 7 post-delivery, respectively. No auditory or vestibular toxicity was observed, and no metabolic alteration of the perilymph was detected. In conclusion, these findings support the translational potential of MB-assisted US for IE drug delivery.