Drug Database
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saxagliptin (Bessin)

✓ Approved

Sino Biopharmaceutical Co., Ltd · DPP4 · 小分子

什么是 saxagliptin?

saxagliptin 是一种小分子,由Sino Biopharmaceutical Co., Ltd研发。该药已获批,用于治疗相关适应症,给药途径:Oral (PO)。

药物档案

商品名Bessin
公司Sino Biopharmaceutical Co., Ltd
药物类别小分子
分子靶点DPP4
给药途径Oral (PO)
状态Approved

作用机制

分子靶点

saxagliptin 作用于 1 个分子靶点:

DPP4dipeptidyl peptidase 4 (CD26, DPPIV)
需要更深入的分析?Noah AI 可解释复杂机制并与同类药物比较。

治疗适应症

saxagliptin 针对 1 个适应症,涉及 1 个治疗领域。

治疗领域疾病/病症分期
Metabolism and nutrition disordersType 2 diabetes mellitus✓ Approved

相关研究文献

PubMedComplementary therapies in clinical practice2026-06-13

Feasibility of remotely delivered Tai Chi on older adults' 24-hour movement behaviors: A crossover randomized controlled trial.

Chen Yingying Y, Ryu Suryeon S, Zeng Nan N, Oginni John J et al.

The feasibility of remotely delivered Tai Chi (TC) interventions and their potential influence on 24-h movement behaviors (physical activity, sedentary time, and sleep) to promote health is limited. Thus, this study tested the feasibility of a remote TC program among community-dwelling older adults and examined its preliminary effects on 24-h movement behavior outcomes. A crossover randomized controlled trial enrolled 44 older adults assigned to either the AB sequence (12 weeks of remotely delivered TC followed by a 2-week washout and 12 weeks of usual care), or the BA sequence (the reverse order). Study feasibility was assessed by recruitment and retention rates, whereas intervention feasibility included intervention adherence, fidelity, and acceptability. The 24-h movement behaviors were tracked by a wearable sensor. Forty-one participants (mean age = 70.8 ± 5.6; 78% women) completed the study and were included in the data analysis. Recruitment and retention rates were 76% and 93%, respectively. Results showed that 85% of participants completed ≥18 of 24 TC sessions, and 94% reported the acceptability of TC as "good" or "excellent". The linear mixed-effects models using period-level change scores showed no statistically significant treatment effects for steps, sleep time, sedentary time, lightly active time, or active time. The findings demonstrate that a remotely delivered TC program is feasible, acceptable among community-dwelling older adults. Future larger trials with rigorous wearable sensor data are needed to determine whether remotely delivered TC can improve 24-h movement behavior patterns.

PMID 42285000
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PubMedJournal of physics. Condensed matter : an Institute of Physics journal2026-06-13

Recent progress on disorder-induced topological phases.

Zhang Dan-Wei DW, Tang Ling-Zhi LZ

Topological states of matter in disordered systems without translation symmetry have attracted great interest in recent years. These states with topological characters are not only robust against certain disorders, but also can be counterintuitively induced by disorders from a topologically trivial phase in the clean limit. In this review, we summarize the current theoretical and experimental progress on disorder-induced topological phases in both condensed-matter and artificial systems. We first introduce the topological Anderson insulators (TAIs) induced by random disorders and their topological characterizations and experimental realizations. We then discuss various extensions of TAIs with unique localization phenomena in quasiperiodic and non-Hermitian systems. We also review the theoretical and experimental studies on the disorder-induced topology in dynamical and many-body systems, including topological Anderson-Thouless pumps, disordered correlated topological insulators and average-symmetry protected topological orders acting as interacting TAI phases. Finally, we conclude the review by highlighting potential directions for future explorations.

PMID 42285139
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PubMedExpert review of vaccines2026-06-13

Recent advances for the pharmaceutical production of highly attenuated poxviruses as viral vector platforms.

Weber Linus G LG, Wolff Michael W MW

Highly attenuated poxviruses serve as potent viral vectors, oncolytic agents, and therapeutic vaccines. They can accommodate and stably maintain a large genomic payload of foreign inserts. Their limited replication in human cells provides an excellent safety profile, but it concomitantly necessitates higher doses of infectious particles for full therapeutic efficacy. We review recent advances in bioprocesses for the pharmaceutical production of poxvirus-based vectors, focusing mainly on the vaccinia virus and the Orf virus. These include upstream processing using highly permissive cell substrates, optimized feeding strategies, and a virus phenotype that facilitates downstream processing. The study explores ongoing challenges and identifies strategies to adapt the downstream process to intensified upstream processes in order to achieve an economic end-to-end production. For notably increased virus yields of up to 2 log after amplification, we propose to replace classic adsorption chromatography by a collective and continuous purification platform for separating the virus from process-related impurities. Filtration operations facilitate process scalability while reducing volumes, which is beneficial for a flow-through polishing to meet pharmaceutical quality attributes. Combined with artificial intelligence modeling, these advancements alleviate financial pressures on healthcare systems and accelerate the production of novel vaccine candidates for clinical use.

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PubMedLuminescence : the journal of biological and chemical luminescence2026-06-13

A Sustainable Spectrofluorimetric Method for Lisinopril Determination Using Erythrosin B Fluorescence Quenching With Mechanistic Characterization, Quantum Mechanical Modeling, and Green Chemistry Evaluation.

Abdelzaher Ahmed M AM, Al Kamaly Omkulthom O, Abdel Rahman Mona A MA

A novel, sensitive, and environmentally sustainable spectrofluorimetric method was developed for lisinopril quantification based on Erythrosin B fluorescence quenching. The method exploits static quenching through ground-state ion-pair complex formation between dianionic Erythrosin B and dicationic lisinopril at pH 6.0. Comprehensive mechanistic investigation employing temperature-dependent Stern-Volmer analysis, thermodynamic studies, Job's method, and PM3 semi-empirical quantum mechanical calculations confirmed the static quenching mechanism driven by electrostatic interactions with binding energy of -6.90 kcal/mol (-28.87 kJ/mol). Under optimized conditions (pH 6.0, 15 μg/mL Erythrosin B, excitation/emission, 533/555 nm), the method exhibited excellent linearity over 0.01-3.0 μg/mL (r = 0.9998) with high sensitivity (LOD, 3.1 ng/mL; LOQ, 9.2 ng/mL). Validation according to ICH Q2(R2) guidelines demonstrated excellent accuracy (99.8 ± 1.119%), precision (RSD < 1.63%), robustness, and selectivity. The method was successfully applied to pharmaceutical tablets (100.02 ± 1.079% recovery) and spiked human plasma (96.19%-105.72% recovery). Comprehensive sustainability assessment using RGB12 (whiteness, 88.0/100) and EPPI (total score, 83.8) confirmed the method's superior environmental sustainability and ideal green profile. The developed method offers significant advantages including commercially available reagents, elimination of derivatization or nanomaterial synthesis, and simple instrumentation, representing an environmentally friendly alternative for routine lisinopril determination in pharmaceutical quality control and bioanalytical applications.

PMID 42286975
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PubMedScientific reports2026-06-13

Optimization algorithm for improving the prediction accuracy of API solubility in green solvent.

Alasiri Ali A, Lahiq Ahmed A AA, Alshehri Abdullah A AA

Supercritical carbon dioxide (SC-CO₂) is widely used as an environmentally friendly solvent in pharmaceutical processing, where accurate prediction of drug solubility is essential for efficient formulation design, extraction processes, and process optimization. However, predicting solubility behavior in supercritical systems remains challenging due to the nonlinear interactions between thermodynamic conditions and molecular properties. In this study, a hybrid artificial intelligence framework is developed to predict the solubility of active pharmaceutical ingredients (APIs) in SC-CO₂ using a curated dataset of more than 350 experimentally reported measurements. The proposed framework integrates interpretable deep learning (TabNet) and histogram-based gradient boosting (HGB) with three metaheuristic optimization algorithms, namely the Attack-Leave Optimizer (ALO), Energy Valley Optimizer (EVO), and Botox Optimization Algorithm (BOA), to improve hyperparameter tuning and predictive performance. Model evaluation was conducted using multiple statistical indicators, five-fold cross-validation, prediction interval bootstrapping, and multi-objective Pareto front analysis to assess accuracy and robustness. Among the evaluated configurations, the EVO-tuned TabNet model demonstrated the best predictive performance, achieving a coefficient of determination of [Formula: see text]along with narrow prediction intervals, indicating strong generalization capability within the studied thermodynamic domain. Statistical analysis using the Kruskal-Wallis test confirmed significant differences between optimizer performances ([Formula: see text]). These findings demonstrate that the proposed hybrid pipeline enhances predictive accuracy and interpretability within the thermodynamic domain represented by the compiled dataset. The framework therefore provides a statistically supported computational tool for assisting solvent selection and formulation analysis in supercritical systems, while broader generalization would benefit from future expansion of experimental solubility datasets.

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PubMedJournal of pharmaceutical and biomedical analysis2026-06-13

A novel electrochemical sensing with MIP for highly selective and sensitive determination of anticancer drug erlotinib.

Erdogan-Kablan Sevilay S, Cetinkaya Ahmet A, Unal M Altay MA, Bellur Atici Esen E et al.

The sensitive and selective determination of targeted anticancer drugs is crucial for pharmaceutical quality control and therapeutic monitoring. Erlotinib (ERL), a tyrosine kinase inhibitor approved by the U.S. Food and Drug Administration (FDA) for the treatment of metastatic or locally advanced non-small cell lung cancer (NSCLC), requires reliable analytical methods due to its clinical importance and potential impurities. In this study, an ultrasensitive nanomaterial-supported molecularly imprinted polymer (MIP)-based electrochemical sensor was rationally designed for the selective detection of ERL. Zinc oxide nanoparticles (ZnONPs) were incorporated to enhance the effective surface area and increase the density of active recognition sites. The polymeric film was synthesized using 3-aminophenyl boronic acid (3-APBA) as the functional monomer, ethylene glycol dimethacrylate (EGDMA) as the cross-linker, 2-hydroxyethyl methacrylate (HEMA) as the base monomer, and 2-hydroxy-2-methylpropiophenone as the initiator. The fabricated 3-APBA/ERL/ZnONPs@MIP-modified glassy carbon electrode (GCE) was characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV). The sensor exhibited a linear response in the range of 1.0 × 10-13-1.0 × 10-12 M (100-1000 fM) with a limit of detection (LOD) of 1.89 × 10-14 M (18.9 fM) and a limit of quantification (LOQ) of 6.30 × 10-14 M (63.0 fM) (r = 0.997). Selectivity and specificity studies demonstrated that ERL could be accurately quantified even in the presence of structurally related drugs and ERL-related impurities at 1000-fold excess, yielding recovery values between 98.40% and 103.76%. The sensor was successfully applied to ERL determination in tablet dosage forms, demonstrating its suitability for pharmaceutical quality control. Furthermore, density functional theory (DFT) and Monte Carlo simulations elucidated the molecular recognition mechanism, revealing a precise "lock-and-key" fit of ERL within the imprinted cavities and supporting a target-induced "site-blocking" sensing mechanism.

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