Current pharmaceutical biotechnology最新文献

The pharmaceutical industry is transforming with the advent of Industry 5.0, which is marked by integrating artificial intelligence (AI) into drug discovery and development. AI technologies, such as machine learning, deep learning, and natural language processing, revolutionize the traditional drug development pipeline by accelerating the identification of novel drug candidates, optimizing clinical trial designs, and personalizing therapies. Moreover, AI models enhance the prediction of drug efficacy, toxicity, and patient responses, minimizing the risk of failure of clinical trials. Nevertheless, despite these advancements, challenges remain in integrating AI into the pharmaceutical workflow, including data quality, regulatory concerns, and the need for interdisciplinary collaboration. This review explores the current state of AI applications in drug discovery, drug formulation and optimization, pharmacokinetics and pharmacodynamics, drug manufacturing and quality control, regulatory compliance and pharmacovigilance. Overall, AI is poised to redefine the landscape of drug discovery and development, fostering a new era of precision medicine and transforming patient outcomes globally, especially in the era of Industry 5.0.

Introduction: Gene transfection techniques have potential therapeutic value in reducing the inflammatory response in atherosclerosis. Atherosclerosis is a chronic inflammatory disease. Its pathological process involves multiple types of cells and signaling pathways.

Methods: In recent years, researchers have used gene transfection techniques to introduce specific genes into vascular or immune cells in order to inhibit inflammatory responses, stabilize plaques, and slow down the process of atherosclerosis. Research progress has shown that gene transfection can exert anti-inflammatory effects through various mechanisms. IL-10 transfection suppresses atherosclerosis by activating the STAT3 pathway, reducing TNF-α and IL-6 expression in macrophages. Conversely, eNOS transfection enhances nitric oxide bioavailability, inhibiting endothelial cell adhesion molecule expression (e.g., VCAM-1) and monocyte recruitment.

Results: Other studies have regulated the expression of inflammation-related genes by transfecting miRNA (tiny RNA), thus inhibiting the inflammatory response of atherosclerosis.

Discussion: Despite preclinical efficacy, clinical translation is hindered by suboptimal vector tropism (e.g., viral vectors exhibit off-target hepatotoxicity) and immune-mediated clearance of non-viral vectors (e.g., liposomes trigger complement activation). Long-term risks of insertional mutagenesis (retroviral vectors) and epigenetic silencing of transgenes further limit durability.

Conclusion: This paper discusses the role and mechanism of gene transfection in reducing the inflammatory response in atherosclerosis.

Introduction: The rise of antimicrobial resistance, coupled with the declining discovery of new antibiotics, has intensified the need for alternative therapeutics. Antimicrobial peptides (AMPs), such as Fowlicidin-1, offer broad-spectrum antimicrobial activity but are limited by their cytotoxic effects, including hemolysis of human erythrocytes.

Method: In this study, Fowlicidin-1 was encapsulated into chitosan nanoparticles formed via ionic gelation. The formulation was optimized for encapsulation efficiency, particle size, and surface charge. Antimicrobial activity was evaluated against resistant bacterial strains, while cytotoxicity was assessed using hemolysis and cell viability assays.

Results: The chitosan nano-carrier system effectively preserved the antimicrobial potency of Fowlicidin-1 and significantly reduced its cytotoxicity. Encapsulated Fowlicidin-1 demonstrated reduced hemolytic activity and improved safety compared to the free peptide.

Discussion: Nano-encapsulation using a chitosan-based delivery system successfully mitigates the cytotoxic limitations of AMPs without compromising antimicrobial efficacy. This approach may enhance the clinical applicability of AMPs as alternatives to traditional antibiotics.

Conclusion: The developed chitosan-based cross-linked nanocarrier system offers a promising strategy to reduce the cytotoxicity of AMPs, supporting their potential as safer and more effective antimicrobial therapeutics in the fight against antibiotic resistance.

Introduction: Atherosclerosis, a chronic inflammatory disease driven by lipid metabolism dysregulation and vascular dysfunction, is a major contributor to cardiovascular diseases (CVDs), which is the leading cause of global mortality. The present study was undertaken to explore the anti-atherosclerosis potential (targeting DPP-IV, ETB, and PPAR-α) of bioactive compounds from Ginkgo biloba L.; the corresponding commercially available drugs, viz. Evogliptin, Bosentan, and Bezafibrate were taken as controls.

Methods: Swiss ADME and Protox-II were utilized to evaluate the safety and applicability of G. biloba compounds. MGL Tools and AutoDock Vina were used for molecular docking, followed by analysis with Discovery Studio Biovia. MD simulation was performed for chosen complexes, and the resulting compound was examined for PPI, GO, and KEGG network enrichment using the Shiny GO server.

Results: Eight compounds were shortlisted by using SwissADME and Protox-II servers, followed by molecular docking studies with AutoDock Vina. Six compounds exhibited stronger binding affinities against DPP-IV compared to Evogliptin (-7.1 kcal/mol), five outperforming Bosentan (- 7.5 kcal/mol) against ETB, and six better than Bezafibrate (-7.5 kcal/mol) against PPAR-α. Postdocking analysis identified Isoginkgetin for both DPP-IV and ETB receptors, while Kaempferol for PPAR-α. MD simulation studies of Isoginkgetin-DPP-IV, Isoginkgetin-ETB, and Kaempferol- PPAR-α resulted in the ETB-Isoginkgetin complex with the most favourable binding stability, rapid equilibration, and consistent hydrogen bonding. Network pharmacology analysis further highlighted Isoginkgetin's ability to modulate key proteins (CYP19A1, ESR2, GSK3B, XDH, PTGS2) associated with crucial CVD-related pathways.

Conclusion: The findings highlight the multi-target therapeutic potential of Isoginkgetin in mitigating the initiation and progression of atherosclerosis.

Introduction: Generalized anxiety disorder (GAD) is a prevalent and intricate mental disorder that significantly impairs the quality of life of patients. Currently, the exact etiology of GAD remains incompletely understood. Consequently, the discovery of novel drug targets for GAD is highly important.

Methods: We obtained cis-eQTL data of druggable genes from the eQTLGen Consortium as the exposure data and GWAS data of GAD from the FinnGen Database as the outcome. The impact of druggable genes on GAD was simulated through Mendelian randomization analysis. Subsequently, a colocalization analysis was conducted to calculate the probability of shared pathogenic variants between the cis-eQTLs of druggable genes and GAD. To further validate our findings, a summary data-based Mendelian randomization (SMR) analysis was carried out.

Results: Mendelian randomization (MR) analysis identified 24 druggable genes with potential causal relationships, among which genetically predicted increased KDM5A levels were associated with a higher risk of GAD (OR=1.0991, 95% CI: 1.0021-1.2056, P=0.0451), suggesting a potential role of KDM5A gene expression in the pathogenesis of GAD. The GAD and KDM5A genes might share a causal variant. The SMR further verified the accuracy of the KDM5A gene.

Discussion: MR analysis identified KDM5A as a promising therapeutic target for GAD, with additional potential from genes, like MERTK and PPT1. However, the effectiveness of the relevant drug targets requires further validation.

Conclusion: This study suggested that the KDM5A gene might be a potential therapeutic target for treating GAD, providing a direction for future drug development in GAD patients.

Introduction: Ganoderma lucidum is considered a medicinal mushroom, as it primarily improves gut health by modulating the gut microbiota. As an abundant source of bioactive metabolites, antioxidants, and industrial enzymes, mushrooms make significant contributions to functional foods, nutrition, and pharmaceuticals. Polysaccharides derived from G. lucidum exhibit prebiotic potential, promoting the growth and activity of beneficial gut microorganisms.

Methods: This review examines the impact of white rot basidiomycetes metabolites on colorectal cancer treatment. We have compiled and analyzed data from PubMed, Google Scholar, and ResearchGate, presenting a comprehensive report with a table for clear understanding.

Results: Evidence from in vivo and in vitro studies demonstrates that G. lucidum has potential as a gastrointestinal cancer inhibitor by inducing pro-apoptosis, autophagy, G0/G1 cell cycle arrest, and immunomodulation.

Discussion: Bioactive metabolites and polysaccharides have prebiotic potential, enhancing the growth and activity of beneficial gut microorganisms that may lower the risk of gastrointestinal cancers by modifying gut bacteria. The prebiotic properties may boost immunity, reduce inflammation, and strengthen intestinal barrier integrity.

Conclusion: The current review explores the therapeutic potential of G. lucidum and other medicinal mushrooms as dietary supplements, focusing on their impact on the gut microbiome and gastrointestinal cancer.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as a global health concern. In recent years, the gut microbiota, often referred to as the body's "second genome," has been recognized as playing a crucial role in the pathogenesis of MASLD. PubMed was searched for articles published in the last decade using keywords like "MASLD," "NAFLD," "gut microbiota," "FXR," and "Trace elements." The progress of the latest NAFLD clinical trial was also reviewed from the Chinese Clinical Trial Registry, organized by clinical phase. In the development of MASLD, the gut microbiota not only participates in regulating host gene expression but also exerts a core influence on immune function and affects the liver's reparative capabilities. Furthermore, the metabolic products of the gut microbiota are involved in the occurrence and development of liver diseases through the gut-liver axis. A diet high in fat can trigger metabolic inflammation, changes in gut microbiota, and abnormalities in metabolic products, all of which may initiate inflammatory responses. The emerging strategies for treating MASLD are surprising. Clinical trial information for chemical drugs was obtained from the Chinese platform for registration and disclosure of drug clinical trials, and it was found that in the current drug development, some drugs have advanced to Phase III clinical trials. The diversity of gut bacteria among individuals and the impact of microbial composition beyond bacteria should not be overlooked. Whether drug therapy combined with dietary patterns is more effective than monotherapy remains to be seen.

Introduction: This study aimed to develop a local drug delivery system using pterostilbene (PTS) flexible nanoliposomes (FNL) to overcome its limitations, such as poor water solubility and instability under light and oxygen. The research focused on optimizing deformability and transdermal delivery using dipotassium glycyrrhizinate and a single-chain surfactant as membrane softeners.

Methods: The encapsulation process and formulation of PTS FNL were systematically optimized through single-factor and orthogonal experiments. The physicochemical properties, stability, and transdermal performance of the optimized FNL were evaluated using dynamic light scattering, transmission electron microscopy (TEM), Turbiscan stability analysis, and in vitro/in vivo permeation studies.

Results: The optimized PTS FNL exhibited high encapsulation efficiency (96.49 ± 0.7%), a particle size of (60.11 ± 0.54 nm), PDI (0.237), a zeta potential of (-10.16 ± 0.54 mV), and good stability at 4°C and 25°C for three months. TEM confirmed spherical morphology, while in vitro studies demonstrated superior skin retention and prolonged permeation compared to PTS nanoliposomes (NL) and GTCC solutions. In vivo tests on human volunteers revealed that 0.4% PTS FNL cream significantly improved skin elasticity and chromaticity over 28 days without adverse effects.

Discussion: The enhanced deformability of PTS FNL contributed to its improved transdermal delivery, making it a promising candidate for cosmetic applications. The study highlights the effectiveness of membrane softeners in optimizing liposomal formulations, though long-term stability under varied conditions warrants further investigation.

Conclusion: The developed PTS FNL system significantly enhances skin permeation and stability, demonstrating great potential for cosmetic use in anti-aging and skin-brightening formulations. This approach provides a viable strategy for improving the delivery of poorly soluble active ingredients.

Introduction: The current pharmaceutical industry has increasingly adopted artificial intelligence (AI), integrating it across the entire industrial chain. While AI improves efficiency and reduces costs, it also faces challenges. This study explores both the technological evolution and contemporary innovation hotspots of AI in pharmacy.

Methods: Methods: This study adopts a fusion analysis of multi-source data, constructing a bidimensional analytical framework based on patented inventions (1990-2024) and research articles (2020-2024) as research objects. The study applies the Latent Dirichlet Allocation (LDA) topic model to analyze the evolution of patent topics and employs CiteSpace to construct keyword knowledge graphs from research articles. By integrating patent and article data to define technical labels, the study identifies research hotspots from the perspective of the pharmaceutical life cycle, enabling cross-validation from both scientific and technical dimensions.

Results: The number of AI-related patents in the pharmaceutical field has grown rapidly over the past five years. Technological topics exhibit a distinct evolutionary trend. Research hotspots span the entire pharmaceutical life cycle, from drug development to clinical delivery. Additionally, potential directions for future technological development have been identified.

Discussion: Research hotspots in the application of AI in pharmaceuticals include target identification, virtual screening, drug delivery, clinical trials, and pharmacovigilance. Precision medicine and explainable AI (XAI)-driven pharmacy modeling are expected to emerge as key directions for future technological development.

Conclusion: AI has already reshaped the pharmaceutical industry through applications across all stages of the pharmaceutical life cycle. It is poised to attract growing research attention and drive innovative applications in the years ahead.