Journal of Pharmaceutical Innovation最新文献

Olmesartan medoxomil (OLM), a widely prescribed antihypertensive agent, suffers from poor solubility and first pass metabolism, which lowers its bioavailability. This work aimed to develop novel cationic nanocarriers (LeciPlex) for OLM to enhance its dissolution and oral bioavailability. A central composite design (CCD) was employed to optimize OLM-loaded LeciPlex (OLM-LPX) formulations. The independent variables included lecithin amount, surfactant amount, and surfactant type. The influence of these factors on particle size (PS), entrapment efficiency (EE), surface charge (ZP), and cumulative in vitro drug release (CR) was thoroughly evaluated and examined. The optimized formulation underwent additional evaluation for ex vivo permeation, morphology, stability, in vivo histopathology, and pharmacokinetic studies. The optimized OLM-LPX exhibited desirable PS (149.23 ± 2.02 nm), ZP (+ 62.03 ± 2.45 mV), EE (82.25 ± 4.63%), and CR (88.87 ± 1.97% after 8 h), aligning well with the predicted CCD values. Ex vivo permeation of optimized OLM-LPX across rabbit intestine showed a cumulative OLM transport of 1973.1 ± 207.9 µg versus 909.9 ± 217.8 µg for OLM suspension, with a permeability coefficient 3.4-fold higher and a 2.17-fold increase in intestinal permeability. Transmission electron microscope images showed spherical-shaped and smooth particles. It also exhibited accepted stability over the predetermined storage period (90 days), showing neither sedimentation nor particle coalescence. The orally administered optimized OLM-LPX showed no evidence for inflammatory signs or mucosal damage within intestinal gut segments under histopathological examination. Pharmacokinetic evaluation in rats demonstrated that OLM-LPX achieved a C_max of 3.48 ± 0.25 µg/mL versus 1.32 ± 0.21 µg/mL for suspension, extended t_max (2 h vs. 1 h), and a markedly enhanced AUC_₀–∞ of 41.17 ± 3.41 µg·mL⁻¹·h compared to 11.48 ± 1.69 µg·mL⁻¹·h, corresponding to a relative bioavailability of 358.62%. Collectively, LPX may serve as an effective nanocarrier for effective oral administration of poorly soluble OLM, contributing to its enhanced bioavailability.

Graphical Abstract

Background

Medicinal plants are rich sources of bioactive compounds with significant antioxidant and antimicrobial properties, making their chemical and biological evaluation essential for discovering natural therapeutic agents.

Objective

The present study investigated the phytochemical composition and biological activities of Cupressus sempervirens stem bark methanolic extract (MECS) and its fractions (ethyl acetate-EACS, n-hexane-NHCS, and aqueous AQCS).

Methods

The crude methanolic extract of stem bark along with its fractions was analyzed for phytochemical composition by Gas Chromatography-Mass Spectrometry (GC-MS), Antioxidant activity was evaluated using DPPH and ABTS assays, while antimicrobial activity was assessed against selected bacterial and fungal strains using the Well Diffusion Method.

Results

GC–MS analysis revealed 20 bioactive compounds, with Bis(2-ethylhexyl) benzene-1,4-dicarboxylate (22.03%), Phenanthren-2-ol (14.34%), and (9Z)-Octadec-9-enoic acid (13.79%) as major constituents. Antioxidant assays (DPPH and ABTS) demonstrated significant radical scavenging activity, with EACS exhibiting the highest potency (IC₅₀ = 15.45 µg/mL for ABTS, 21.02 µg/mL for DPPH). Antibacterial screening showed concentration-dependent inhibition, with MECS displaying broad-spectrum efficacy against Proteus mirabilis (19.0 ± 1.0 mm) and Pseudomonas aeruginosa (16.25 ± 0.75 mm), while EACS was most active against MRSA (16.5 ± 0.5 mm). Antifungal assays highlighted EACS's effectiveness against Alternaria alternata (16.25 mm) and Aspergillus niger (13.75 mm), though all extracts were less potent than standard antibiotics.

Conclusion

These findings highlight C. sempervirens as a promising source of antimicrobial and antioxidant compounds, warranting further phytochemical exploration for therapeutic applications.

Oxiconazole nitrate (OXN) is an imidazole-derived antifungal agent used topically for the treatment of superficial fungal infections, particularly those caused by Candida species and dermatophytes. In this study, a novel hydrogel formulation containing OXN, a choline chloride: propylene glycol (CC: PG)–based green solvent, and poloxamer 407 was developed and extensively characterized as a multifunctional topical delivery system. The formulation was evaluated for thermoresponsive viscosity behavior, drug release, cytocompatibility, antifungal efficacy, and anti-inflammatory activity. Viscosity analysis revealed that, contrary to conventional poloxamer gels, the formulation exhibited a decrease in viscosity with increasing temperature, which may be attributed to a green solvent-mediated suppression of micelle formation. This behavior allowed the hydrogel to remain semi-solid at room temperature while becoming more spreadable at body temperature. In vitro release studies demonstrated that the OXN-loaded hydrogel released 90.98 ± 7.52% of OXN within 24 h, significantly higher than the marketed cream formulation (25.74 ± 4.00%). MTT assays confirmed high cell viability (133.65 ± 1.54% in HEK293 and 89.35 ± 1.97% in HaCaT cells), indicating excellent biocompatibility and an increase in metabolic activity that may be associated with the green solvent. Antifungal testing showed enhanced inhibition zones against Candida albicans and Candida glabrata, with minimal activity against Lactobacillus crispatus, suggesting possible microbiota-sparing properties. Furthermore, the hydrogel significantly reduced LPS-induced TNF-α and IL-1β expression by 71.5% and 42.3%, respectively, in RAW 264.7 macrophages. These findings support the potential of the developed OXN-loaded hydrogel (P4-P21) as an effective, biocompatible, anti-inflammatory, and microbiota-sparing topical formulation for the treatment of fungal infections.

Background

The SARS-CoV-2 nsp10-nsp16 complex, a critical 2’-O-methyltransferase (MTase), plays a pivotal role in viral RNA capping, enabling immune evasion and efficient replication.

Methods

Our study employed a structure-based drug design (SBDD) approach to identify computationally prioritized candidates targeting the nsp10-nsp16 complex. Virtual screening of the ZINC20 In-Stock database using both AutoDock Vina and KarmaDock, one based on physics-driven scoring and the other on deep learning, identified six leading candidates with high affinity for the nsp16 active site.

Results

Among them, ZINC5222796, ZINC253388707, and ZINC100829855 showed the strongest binding affinities to the nsp16 active site. Among these, ZINC5222796, ZINC253388707, and ZINC100829855 demonstrated the highest binding affinities, with MM-GBSA binding free energies of -40.0 ± 0.09 kcal/mol, -37.3 ± 0.07 kcal/mol, and − 36.6 ± 0.09 kcal/mol, respectively, surpassing the control compound tubercidin (-27.7 ± 0.10 kcal/mol). Triplicate molecular dynamics (MD) simulations confirmed their robust stability, with low mean root mean square deviation (RMSD) and minimal structural fluctuations. These inhibitors exhibited extensive hydrogen bonding with critical active site residues, including ASP99, CYS115, and TYR132, contributing to their enhanced stability. Per-residue energy decomposition and DFT calculations further supported these findings, highlighting consistent interactions with key residues and favorable electronic properties that contribute to stable and high-affinity binding. The selected compounds demonstrated both stable binding and favorable energetics, surpassing the reference ligand in overall performance.

Conclusion

Collectively, these results indicate that the identified molecules stabilize key catalytic residues and maintain the conformational integrity of the active site throughout MD trajectories. Their favorable electronic profiles and sustained intermolecular contacts suggest potential to inhibit viral RNA capping by targeting the nsp10–nsp16 interface. This computational framework provides a foundation for rational optimization and experimental validation of nsp16-directed antiviral candidates.

Curcuma xanthorrhiza Roxb. (Javanese turmeric) contains curcumin, a bioactive compound possessed several biological activities including antibacterial. However, its clinical application is limited due to poor water solubility, chemical instability, and low bioavailability. This study aimed to develop, characterize, and evaluate niosomes loaded with C xanthorrhiza extract for enhanced antibacterial activity. Niosomes were prepared using the thin-layer hydration method with varying ratios of Span 60 and cholesterol. These formulations were evaluated for their characteristics, entrapment efficiency (EE), physical stability, in vitro drug release, and antibacterial activity. The optimized formulation F1 containing Span 60 and cholesterol (1:2) showed acceptable % EE (95.27), optimum particle size (10.58 μm), the zeta potential was − 79.3 along with a sustained release, displayed a spherical niosome morphology and possessed antibacterial activity against Propionibacterium acnes, Staphylococcus epidermidis, and S. aureus with the Minimum Inhibitory Concentrations (MICs) in the range 78.12 to 312.50 µg/mL. The optimized formulation was incorporated into gel. The formulation met the required physical parameters, long storage stability, displayed a more controlled and stable release profile with minimal flux variation. The niosome gel followed the Korsmeyer–Peppas kinetic model, indicating a non-Fickian diffusion mechanism involving both diffusion and polymer matrix relaxation. The gel significantly inhibited the growth of P. acnes, S. epidermidis, and S. aureus. In conclusion, noisome gel demonstrated favorable physicochemical properties, sustained release, improved gel stability and antibacterial performance. This result emphasized the potential of niosomal gels as controlled-release transdermal formulations for acne treatment.

Solid lipid nanoparticles (SLNs) exhibit excellent potential as a drug delivery system in treating several cancers including gastrointestinal (GI) malignancies. SLNs offer potential advantages over conventional drug delivery methods in terms of their superior physicochemical and biological characteristics. In GI malignancies, SLNs are advantageous for advanced targeting, decreased systemic toxicity, and increased therapeutic effect of anticancer drugs due to their distinctive physicochemical properties, such as biocompatibility, ability to entrap both hydrophilic and lipophilic drugs, and sustained release potential. This review elaborates the unique applications of SLNs in treating GI malignancies including Esophageal, gastric, colorectal, liver, and pancreatic cancers, focusing on their ability to overcome the limitations of conventional modules such as poor bioavailability, rapid drug metabolism, decreased intestinal absorption and resistance mechanisms developed by the tumor cells. Through the use of SLNs for delivering chemotherapeutic drugs, RNA-based therapies, and immunomodulators, several advantages are offered in the management of GI cancers in terms of improved clinical outcomes and decreased side effects. The challenges and future perspectives for the clinical translation of SLNs in GI malignancies are also apprised, highlighting the need for research and optimization of formulation strategies. SLN-based nanocarrier systems offer a unique platform for prospective applications in the delivery of anticancer drugs in the form of targeted therapeutics.

Purpose

Breast cancer is a leading cause of female cancer mortality. Caffeic acid (CA), a plant-derived polyphenol, demonstrates anticancer potential, but has limited clinical utility due to poor solubility, instability, and quick elimination.

Methods

This study presents the first QbD-based optimization of caffeic acid (CA) cubosomes (CA-CN) for breast cancer. To study the impact of glyceryl monooleate (GMO) concentration, Poloxamer 407 concentration and sonication time on the particle size, zeta potential and entrapment efficiency (EE), a three-factor three-level Box- Behnken Design (BBD) was used.

Results

The optimized formulation exhibited particle size of 102.9 nm, EE of 98.9% and zeta potential of -31 mV showing good colloidal stability. In the design study it was seen that the increase in Poloxamer 407 concentration and sonication time decreased particle size and EE considerably and that the increase in GMO concentration provided larger particle and moderate drug encapsulation. The successful encapsulation and a transition of CA to an amorphous form favoring its solubility enhancement were proved by FTIR, XRD, and DSC researches. CA-CNs showed 87.4%. drug release after 24 h. The pharmacokinetic profile in rabbits revealed that CA-CN was associated with 3.08-fold higher bioavailability than pure CA.

Conclusion

The cubosomal system improved CA’s physicochemical and pharmacokinetic properties, indicating its potential as a nanocarrier for breast cancer. Future research may focus on active targeting and clinical-scale development.

Purpose

Drug-excipient interactions significantly influence the stability, bioavailability, and therapeutic efficacy of pharmaceutical formulations. Although effective, conventional stability studies and advanced analytical techniques are often resource-intensive and time-consuming. This study introduces Drug-Excipient Interaction tool named as “DE-Interact”, an Artificial Intelligence based predictive tool designed to rapidly predict drug-excipient compatibility, thereby expediting formulation development.

Methods

The Drug-Excipient Interact model was developed using PubChem chemical fingerprints as molecular descriptors and trained with an artificial neural network. A curated dataset of drug-excipient pairs was divided into training, test, and validation sets. The tool’s predictions were experimentally validated through Differential scanning calorimetry, Fourier transform infrared spectroscopy, Thin layer chromatography, High-performance thin layer chromatography, and High-pressure liquid chromatography. Three combinations: Brinzolamide-Polyethylene glycol, Domperidone-Citric Acid, and Olanzapine-Lactose were selected as case studies.

Results

The Drug Excipient Interact model accurately predicted incompatibilities for the selected combinations, which were confirmed by experimental analyses. Differential scanning calorimetry revealed altered thermal behaviour in drug-excipient mixtures, Fourier transform infrared spectra revealed disrupted functional group signals, and chromatographic studies indicated degradation or altered chemical profiles over time. These validations support the predictive robustness of the tool.

Conclusions

Drug Excipient Interact demonstrates strong predictive performance in identifying drug-excipient incompatibilities, reducing the reliance on prolonged stability testing. By integrating computational and experimental approaches, the model provides a cost-effective, scalable, and time-efficient solution for early formulation screening. This Artificial Intelligence driven framework has the potential to accelerate pharmaceutical product development and optimize excipient selection strategies.