Journal of Pharmaceutical Innovation最新文献

Current research work aimed to develop and characterise of liquid crystalline nanoparticles (LCNPs) physically blended dual-LCNP formulation with palbociclib (PCB) and letrozole (LTZ) to improve therapeutic performance in treatment of breast cancer. Drug-loaded LCNPs were prepared using glyceryl monooleate (GMO) as the lipid phase and Poloxamer-407 as the stabilizer via a high-energy emulsification followed by probe sonication. A 3² full factorial design was applied to systematically optimize critical formulation variables affecting particle size and entrapment efficiency. The optimized LCNs of dispersions were combined to obtain the final formulation (PLNs-9) and characterized for morphology (TEM), thermal behaviour (DSC), crystallinity (XRD), and drug–excipient compatibility (FTIR). The PLNs-9 exhibited nanoscale particle size (144.2 ± 5.3 nm) with high entrapment efficiencies (PCB 95.54 ± 3.57%, LTZ 84.35 ± 2.86%). Solid-state analyses confirmed molecular dispersion of drugs within the lipid matrix. In vitro release studies demonstrated sustained drug release under physiological conditions. Cytotoxicity studies in MCF-7 breast cancer cells revealed significantly enhanced antiproliferative activity of PLNs-9 (IC₅₀ = 10.56 ± 1.34 µg; p < 0.001) compared with individual drugs and their physical combination, accompanied by increased apoptotic cell populations and pronounced G2/M phase arrest. Pharmacokinetic evaluation demonstrated prolonged systemic circulation and approximately 2-fold enhancement in relative bioavailability compared to both PCB and LTZ. These findings suggest that the developed PLNs-9 containing PCB and LTZ combination represents a promising synergistic nanotherapeutic platform for breast cancer management.

Multiple myeloma (MM) is an incurable plasma cell malignancy characterized by dysregulation of CD38, a multifunctional ectoenzyme and receptor critical for tumor progression and immune modulation. While monoclonal antibodies targeting CD38 have improved clinical outcomes, small-molecule inhibitors remain scarce, limiting alternative therapeutic strategies. In this study, we employed a comprehensive in silico approach to identify drug-like, non-toxic marine Cyanobacterial metabolites as promising potential CD38 inhibitors. A total of 1085 MM-associated genes were intersected with 357 CD38-interacting genes to identify 207 MM-associated targets, which were enriched in immune-regulatory pathways. The CD38 binding pocket was characterized, and molecular docking screened Cyanobacterial metabolites for binding affinity and drug-likeness, identifying top candidates compliant with Lipinski, Ghose, Veber, Egan, and Muegge rules. Based on binding affinity, the selected drug-like, non-toxic metabolites (CyanoMetDB_1359, CyanoMetDB_2811, and CyanoMetDB_2812) exhibited favorable interactions with key residues, including TRP125, LEU145, TRP176, and THR221, overlapping with co-crystallized ligand interactions. Molecular dynamics simulations over 200 ns revealed stable protein-ligand complexes, with consistent RMSD, RMSF, Rg, SASA, distance, and hydrogen-bond profiles. Extensive principal component analysis and free energy landscapes confirmed conformational stability and minimal fluctuation. MM-PBSA calculations indicated favorable binding free energies, with residue-based decomposition suggesting critical stabilizing interactions. Collectively, this study identifies rare, marine-derived small-molecule candidates capable of effectively targeting CD38, bridging marine natural product chemistry with MM therapeutics. These findings provide a foundation for future experimental validation and development of small-molecule CD38 inhibitors derived from natural sources, with potential anti-myeloma activity.

Background

Colorectal cancer (CRC) remains a major global health burden, emphasizing the need for targeted therapies with improved efficacy and fewer adverse effects. Quercetin and resveratrol possess substantial anticancer activity, but their therapeutic application is limited by poor bioavailability, instability, and rapid degradation.

Methods

Quercetin- and resveratrol-co-loaded polymeric nanoparticles (QRNPs) were formulated using poly(lactic-co-glycolic acid) (PLGA) and D-α-tocopheryl polyethylene glycol succinate (TPGS). The optimized formulation was evaluated for particle size, zeta potential, encapsulation efficiency, morphology, drug–polymer compatibility, pH-dependent drug release, gastrointestinal stability, cellular uptake, cytotoxicity, and apoptosis in Caco-2 colorectal cancer cells.

Results

Optimized QRNPs showed a particle size of 174–177 nm, zeta potential of approximately −22 to −24 mV, and encapsulation efficiency above 80%. FTIR analysis confirmed drug–polymer compatibility, while HR-TEM revealed uniform spherical morphology. Drug-release studies demonstrated minimal release at pH 7.4 and increased release at pH 5.5, indicating preferential release under acidic tumor-like conditions. QRNPs also remained stable in simulated gastrointestinal fluids, demonstrating formulation robustness. Compared with free quercetin and resveratrol, QRNPs produced greater cytotoxicity, with CC₅₀ values of 48.84 μg/mL at 24 h and 32.75 μg/mL at 48 h. Fluorescence imaging demonstrated enhanced cellular uptake, and Annexin V-FITC analysis confirmed increased apoptosis in treated cells.

Conclusion

PLGA–TPGS-based quercetin–resveratrol nanoparticles improved drug stability, cellular uptake, pH-responsive release, gastrointestinal robustness, and in-vitro anticancer activity. These findings support their potential as a promising nanocarrier system for improving colorectal cancer therapy through efficient co delivery of quercetin and resveratrol, while potentially reducing limitations of free drugs.

Graphical Abstract

Background

Parkinson’s Disease is the second most common neurodegenerative disorder worldwide. Although levodopa and monoamine oxidase-B (MAO-B) inhibitors remain the cornerstone of symptomatic management, oral administration is often limited by poor brain targeting and restricted penetration across the blood–brain barrier. The present study aimed to develop and optimize a thermoresponsive nasal in situ gel of Rasagiline Mesylate (RM) to facilitate direct nose-to-brain delivery.

Materials and Methods

A Central Composite Design (CCD) was employed to optimize the formulation. Poloxamer 407 (A: 15–30%, including axial points of 11.89 and 33.11%) and dodecyl maltoside (B: 1.0–2.0%, including axial points of 0.79 and 2.21%) were selected as independent variables, while gelation time, mucoadhesive strength, and permeation coefficient were considered response variables. The developed formulations were characterized for gelation time, mucoadhesive strength, drug content, pH, gelation temperature, viscosity, in vitro permeation, droplet size distribution, and plume geometry.

Results

The optimized formulation (RM1; 22.5% Poloxamer 407 and 1.5% dodecyl maltoside) demonstrated rapid thermogelation at physiological temperature (30.21 s), favourable mucoadhesive strength (~ 1615.8 dyne/cm²), and an enhanced permeation coefficient (0.0029 cm/s). In contrast, formulations containing higher polymer concentrations (RM10; 30% Poloxamer 407 and 2% dodecyl maltoside) exhibited prolonged gelation and reduced permeation performance. All formulations maintained a pH of approximately 7.3, indicating suitability for nasal administration. The optimized gel also exhibited acceptable spray characteristics, viscosity, and drug content uniformity.

Conclusion

The optimized thermosensitive nasal in situ gel of rasagiline mesylate demonstrated desirable physicochemical properties, mucoadhesion, and permeation behaviour, supporting its potential as a non-invasive nose-to-brain delivery platform. This approach may enhance central nervous system targeting of MAO-B inhibitors and represents a promising strategy for improving therapeutic outcomes in Parkinson’s disease.

Purpose

This study aimed to investigate the effect of liraglutide and metformin as monotherapies on the hormonal, metabolic and clinical parameters of Poly Cystic Ovary Syndrome (PCOS). Participants were assigned to receive either Liraglutide (gradually titrated up to 3.0 mg/day as tolerated), Metformin (1000 mg/day), or standard lifestyle modification as a control group for 6 months.

Methods

A randomized, parallel, clinical trial was conducted on 150 patients (50 per group) who completed the study, out of 183 initially randomized patients diagnosed with PCOS.

Results

Out of 183 randomized patients, 150 completed the 24-week protocol (n = 50 per group). Most baseline characteristics were comparable across groups. Following 24 weeks of treatment, baseline-adjusted linear regression demonstrated that liraglutide induced significantly greater weight reduction compared to control (adjusted mean difference: -10.13 kg, FDR-adjusted p < 0.001). Furthermore, liraglutide yielded substantial improvements in insulin resistance, as evidenced by a significantly lower HOMA-IR compared to control (adjusted mean difference: -0.58, FDR-adjusted p < 0.001). Menstrual cycle regularity markedly improved in the liraglutide group (76.0%) compared to metformin (50.0%) and control (32.0%) (p < 0.001). Clinical pregnancy rates were 29.0% Control, 65.7% Liraglutide, 52.9% Metformin; overall between-group difference remained significant after FDR correction (χ²=9.026, FDR-adjusted p=0.044). Nausea, heartburn, and constipation were more frequent with liraglutide than metformin.

Conclusion

Liraglutide is significantly more effective than metformin in improving body weight, glycemic control, and menstrual frequency in women with PCOS and metabolic dysfunction. These findings support liraglutide as a primary therapeutic approach, particularly in obesity-associated PCOS. It was registered at ClinicalTrials.gov under the identifier NCT05965908, registered on July 20, 2023.

The study examined the effect of DNA conjugation on the solubility of a drug in an HPMC polymeric film. The study found that incorporating DNA extract in the film improved drug solubility. The formulation NHE5, with 20% bioplasticizer, showed better drug release compared to other formulations. FTIR and DSC and XRD analyses were carried out. This study indicates that a promising development in drug delivery technology is DNA conjugation to HPMC polymeric films. DNA-HPMC conjugates can enhance DNA-functionalized polymers, promizing improved drug delivery systems and maximizing therapeutic efficacy in pharmaceutical formulations.

Graphical Abstract

Purpose

Wound healing remains a major clinical challenge, particularly in conditions characterized by excessive inflammation and impaired angiogenesis. To address this, the present study was designed to develop and evaluate biocompatible, eco-friendly nano-gels that modulate inflammation and enhance vascularization to accelerate tissue repair.

Methods

Three Holothuria atra extract-loaded nano-systems, chitosan nanoparticles (CS NPs), silver nanoparticles (Ag NPs), and chitosan-coated silver nanoparticles (CS-Ag NPs), were green-synthesized, incorporated into a thermo-responsive poloxamer 407/sodium hyaluronate in situ gel, and evaluated for wound-healing efficacy. Network pharmacology was applied to systematically decipher the multi-target mechanisms of H. atra bioactives and guide biomarker selection.

Results

Network pharmacology identified MAPK1, IL6, AKT1, TNF, and VEGFA as central hub genes prominently enriched in the MAPK, PI3K-Akt, TNF-α, and VEGF signaling pathways, highlighting the multi-target mechanism of H. atra bioactives. Physicochemical characterization demonstrated an optimal gelling temperature (32–34 °C), rapid gelation time (50–55 s), skin-compatible pH (5.8–6.2), and pseudoplastic rheological behavior. In vitro release studies confirmed sustained drug release from the nano-gel formulations compared to the unformulated extract solution, with the CS-Ag NP gel exhibiting superior controlled-release performance. In a Sprague-Dawley rat burn model, the nano-gel formulations significantly accelerated wound closure; the H. atra-CS-Ag NP gel achieved a leading wound contraction of 71.72 ± 2.5% by day 12, comparable to the commercial standard HYALO^® 4 Control (70.18 ± 2.9%). Biochemical analysis revealed significant downregulation of pro-inflammatory cytokines (TNF-α and IL-6) alongside elevated expression of angiogenic and repair markers (VEGFA, AKT1, and MAPK1). Furthermore, in vitro–in vivo correlation (IVIVC) analysis demonstrated strong linear relationships between in vitro dissolution efficiency and network pharmacology-guided biomarkers (r² ≥ 0.922, p ≤ 0.05), confirming a novel systems-level therapeutic approach.

Conclusion

Overall, integrating marine-derived bioactives, silver-chitosan nanotechnology, and thermo-responsive hydrogels offers a promising synergistic platform for advanced wound therapy.

Background

Nitrosamine impurities are a significant pharmaceutical quality concern because of their potential mutagenic and carcinogenic effects. Sensitive and reliable analytical methods are required for their determination in pharmaceutical dosage forms.

Objective

This study aimed to develop and validate a sensitive and selective ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS) method for the trace-level determination of N-nitrosochlordiazepoxide (NNC) in chlordiazepoxide hydrochloride capsule dosage forms.

Methods

Chromatographic separation was achieved using an X-Select HSS C18 XP column (150 × 4.6 mm, 3.5 μm) with gradient elution. Detection was performed using a triple quadrupole mass spectrometer in positive electrospray ionization mode with multiple reaction monitoring (MRM) at m/z 329.10 → 282.10. The method was validated for specificity, linearity, sensitivity, precision, accuracy, solution stability, and filter compatibility in accordance with ICH Q2(R2) recommendations.

Results

The method demonstrated no interference from blank, placebo, or formulation matrix components. Linearity was established over the concentration range of 0.1732–0.6929 ppm, with a coefficient of determination (R²) of 1.000. The limit of detection (LOD) and limit of quantification (LOQ) were 0.052 and 0.1732 ppm, respectively. Method precision and intermediate precision showed %RSD values of 14.1% and 1.2%, respectively, with a cumulative %RSD of 10.4%. Accuracy studies demonstrated mean recoveries of 85–86% across the LOQ, 100%, and 200% concentration levels, with %RSD values of 0.7–1.1%. Standard and sample solutions remained stable for 13 h and 2 h, respectively, under refrigerated conditions. Analysis of commercial 10 mg and 25 mg capsule samples showed that NNC was not detected in any of the tested batches.

Conclusion

The developed UHPLC–MS/MS method demonstrated sensitivity and specificity for trace-level NNC determination in chlordiazepoxide hydrochloride capsule dosage forms. Although the method showed good intermediate precision and consistent recovery, the observed method-precision variability and potential under-recovery should be considered when interpreting quantitative results. The method was successfully applied to the tested commercial capsule batches, in which NNC was not detected under the analytical conditions employed.

Graphical Abstract

Purpose

Loratadine, a Biopharmaceutics Classification System (BCS) Class II antihistamine, exhibits dissolution-limited oral delivery due to poor aqueous solubility. This study aimed to develop a hybrid orodispersible tablet (ODT) platform by incorporating a loratadine nanosuspension into a freeze-dried porous matrix to enhance early in vitro dissolution performance.

Methods

A loratadine nanosuspension was prepared using a modified solvent–antisolvent precipitation method combined with high-shear homogenization and characterized for particle size distribution and zeta potential. Conventional ODTs containing raw loratadine and Nano-ODTs incorporating the nanosuspension were prepared using the same mannitol-based freeze-dried matrix. The formulations were evaluated by FTIR, DSC, SEM, disintegration testing, and in vitro dissolution studies.

Results

The pre-lyophilization nanosuspension showed a Z-average diameter of 148.3 nm, PDI of 0.609, and zeta potential of − 26.5 mV. FTIR and DSC analyses indicated compatibility of formulation components and differences in thermal behavior among the formulations. The Nano-ODT exhibited rapid disintegration and higher early loratadine release compared with the conventional ODT under the selected dissolution conditions.

Conclusion

The developed hybrid Nano-ODT platform successfully combined nanosuspension technology with a freeze-dried porous matrix, resulting in improved early in vitro dissolution performance compared with the conventional ODT. These findings support the potential of this approach for improving dissolution-limited delivery of poorly soluble drugs.

Purpose

Monitoring of complex bioprocesses is critical for ensuring product quality in biopharmaceutical manufacturing. This study systematically evaluates the potential of benchtop ¹H NMR (80 MHz) combined with machine learning as a robust process analytical technology (PAT) tool for bioprocess monitoring.

Methods

A total of 128 samples from eight industrial-scale (1,500 L) CHO-K1 cell culture batches producing Trastuzumab biosimilar were analyzed to acquire both 80 MHz and 600 MHz ¹H NMR spectra. Six batches served as training set and two batches as test set. Lasso, Ridge, PLS, and LightGBM models were built with 5-fold cross-validation to predict 36 metabolites, six metal ions, viable cell density (VCD), viability, and antibody titer.

Results

Lasso and PLS models achieved excellent predictions for 36 metabolites (R² > 0.90, RPD > 3.3) using 80 MHz NMR, comparable to 600 MHz results. Furthermore, our framework enabled the indirect monitoring of indicators that are not directly detectable by ¹H NMR under our experimental conditions, including antibody titer, VCD, and metal ions, by leveraging biological correlations. Notably, the 80 MHz Lasso model outperformed its 600 MHz counterpart in predicting antibody titers on the test set (R² = 0.959), benefiting from reduced data complexity in small-sample modeling. Feature importance analysis revealed that the Lasso models captured chemically meaningful signals aligning with standard metabolite peak positions.

Conclusion

Benchtop NMR coupled with Lasso regression provides a low-cost, information-rich, and interpretable at-line monitoring tool for industrial CHO cell cultures. This approach is particularly advantageous for small-sample scenarios and supports multi-parameter process fingerprinting in biopharmaceutical manufacturing.