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相关概念视频

Drug Delivery: Overview01:16

Drug Delivery: Overview

426
The selection of a drug's delivery route depends upon its physicochemical properties, including lipid or water solubility and ionization, as well as the therapeutic requirement, such as immediate or sustained effect. These routes can be divided into three primary categories: enteral, parenteral, and topical.
Enteral delivery involves administering drugs directly through swallowing, sublingual placement, or buccal application. Orally administered drugs predominantly navigate the...
426
Drug Delivery: Enteral Route01:18

Drug Delivery: Enteral Route

729
The enteral drug administration involves three primary routes: oral, sublingual, and buccal. Oral ingestion is the most prevalent, safe, economical, and convenient method for drug administration. However, it has certain drawbacks, including limited absorption due to the drug's low water solubility or poor membrane permeability, possible emesis from GI mucosa irritation, destruction of drugs by digestive enzymes or low gastric pH, and irregular absorption along with food or other drugs.
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Generation of Alginate Microspheres for Biomedical Applications
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基于酸盐和康杰克的新型核心外气凝配方用于药物输送Glucomannan:使用人工智能工具的理性设计.

Carlos Illanes-Bordomás1, Mariana Landin1, Carlos A García-González1

  • 1AerogelsLab, I+D Farma Group (GI-1645), Department of Pharmacology, Pharmacy and Pharmaceutical Technology, iMATUS and Health Research Institute of Santiago de Compostela (IDIS), Universidade de Santiago de Compostela, E-15782 Santiago de Compostela, Spain.

Polymers
|July 30, 2025
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概括

创建了新型的阿尔金酸盐-康雅克葡萄甘气凝颗粒,用于药物输送. 人工智能优化实现了理想的水凝形成,产生了具有高表面积的粒子,但药物释放需要进一步修改.

关键词:
气凝是一种气凝.酸是一种酸.人工智能工具的人工智能工具有涂层的颗粒.康杰克葡萄康曼南 (glucomannan) 是一种葡萄糖.有孔的粒子是有孔的粒子.超临界的二氧化碳.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 生物材料工程 生物材料工程
  • 药物输送系统 药物输送系统

背景情况:

  • 开发有效的药物输送系统需要精确控制颗粒制造.
  • 酸和康杰克葡萄甘是生物相容的聚合物,具有控制释放应用的潜力.
  • 空气辅助的同轴冲压为创建复杂粒子结构提供了一种方法.

研究的目的:

  • 通过使用空气辅助的同轴冲压来研究和优化制造酸盐-康雅克葡萄康曼南核心外气凝颗粒.
  • 评估制造的气凝颗粒的结构性质和药物加载/释放特征.
  • 展示AI驱动优化对复杂生物材料制造的实用性.

主要方法:

  • 使用空气辅助的同轴冲压制造核心外气凝颗粒.
  • 使用混合人工神经网络和遗传算法优化六个处理变量 (聚合物度,压力,气流,喷嘴配置).
  • 颗粒大小分布,形态,特定表面积 (通过BET分析) 和药物释放概况 (万科米辛化物,德克萨米基) 的表征.

主要成果:

  • 人工智能优化实现了对水凝形成100%的理想解决方案.
  • 在超临界二氧化碳干燥后,最佳颗粒呈现出日志正常尺寸分布 (平均直径1.57毫米) 和高特定表面积 (201米2/克).
  • 药物加载是成功的,观察到德克萨的突发释放 (在10分钟内80%),以及胺的中位依赖释放.

结论:

  • 使用AI优化的空气辅助同轴冲压,可以成功制造酸-酸glucomannan气凝颗粒.
  • 气凝具有有利的结构特性,可用于药物输送应用.
  • 涂层修改是必要的,以实现所需的药物释放动力学,特别是持续释放.