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Related Concept Videos

Modified-Release Drug Delivery Systems: Site-Targeted01:24

Modified-Release Drug Delivery Systems: Site-Targeted

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Site-targeted drug delivery systems enhance therapeutic efficacy while minimizing systemic toxicity and treatment costs. Unlike conventional methods, these systems ensure precise drug delivery, improving bioavailability and reducing side effects. Targeted drug delivery is classified into three levels. First-order targeting directs drugs to the capillary beds of specific organs or tissues. Second-order targets specific cell types, such as tumor cells, using receptor-mediated interactions.
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Drug-Receptor Interaction: Antagonist01:28

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An antagonist is a drug that binds strongly to a receptor without activating it. An antagonist prevents other molecules, such as neurotransmitters or hormones, from binding to the receptor and triggering a cellular response. Such interaction effectively hinders the normal physiological processes mediated by the receptor, resulting in various pharmacological effects depending on the specific receptor targeted.
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Drug Metabolism: Phase II Reactions01:14

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Phase II reactions are essential for the detoxification and elimination of drugs from the body. These reactions involve the conjugation of parent drugs or their phase I metabolites with endogenous molecules, resulting in more hydrophilic drug conjugates. The primary conjugation reactions in this phase are sulfation and glucuronidation. Both sulfation and glucuronidation typically produce biologically inactive metabolites. However, in some cases involving prodrugs, active metabolites may be...
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Modified-Release Drug Delivery Systems: Rate-Programmed I01:22

Modified-Release Drug Delivery Systems: Rate-Programmed I

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Rate-programmed drug delivery systems (DDS) are designed to release drugs at specific, controlled rates to maintain consistent therapeutic levels. These systems are categorized based on their release mechanisms, including dissolution-controlled DDS, diffusion-controlled DDS, and combined dissolution-diffusion-controlled DDS.In dissolution-controlled DDS, the release rate depends on the slow dissolution of the drug itself or the surrounding matrix. Drugs with inherently slow dissolution rates,...
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Modified-Release Drug Delivery Systems: Rate-Programmed II01:19

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Rate-programmed drug delivery systems release drugs in a controlled manner to maintain therapeutic levels. Three main designs include reservoir, matrix, and hybrid systems.Reservoir systems consist of a drug core enclosed within a membrane that controls drug release. In non-swelling reservoir systems, polymers like ethyl cellulose or polymethacrylates are used. These do not hydrate in aqueous media and control release through membrane thickness, porosity, or insolubility. This type includes...
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Drug-Receptor Interactions01:29

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Drug-receptor interaction describes the binding of receptors by drugs, but not all drug-receptor interactions result in activation and tissue response. For instance, the binding of agonists activates the receptor to generate a cellular reaction, while antagonists bind to receptors without causing their activation.
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DRHIN: An Integrated and Interactive Web Server for Drug Repositioning.

Bowei Zhao1, Dongxu Li2, Yue Yang2

  • 1College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.

Journal of Chemical Information and Modeling
|April 19, 2026
PubMed
Summary
This summary is machine-generated.

Drug repositioning (DR) accelerates new therapeutic uses for existing drugs by analyzing complex biological networks. DRHIN, a novel web server, employs deep learning on heterogeneous information networks (HINs) for advanced drug discovery.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Drug Discovery

Background:

  • Drug repositioning (DR) offers a faster, safer approach to identifying new therapeutic applications for existing drugs.
  • Analyzing large-scale multiomics data and complex biological networks remains a significant challenge for current DR tools.

Purpose of the Study:

  • To develop DRHIN, an integrated, interactive web server for advanced drug repositioning using deep learning on heterogeneous information networks (HINs).
  • To provide a user-friendly, code-free platform for discovering drug-disease associations and identifying potential therapies.

Main Methods:

  • Integration of multiomics data (transcriptomics, proteomics, microbiome) into diverse HINs with eight biological entities and 19 association types.
  • Application of 19 state-of-the-art graph representation learning algorithms for network analysis and prediction.
  • Leveraging high-performance computing for efficient processing of large-scale biological networks.

Main Results:

  • DRHIN successfully integrates multiomics data to build comprehensive HINs for elucidating molecular mechanisms.
  • The platform supports three key predictive tasks: drug-disease association discovery, drug repurposing, and identification of potential therapies.
  • DRHIN demonstrates efficient processing of million-scale networks, ensuring practical applicability.

Conclusions:

  • DRHIN provides an accessible and reproducible solution for drug repositioning by overcoming the limitations of existing tools in analyzing complex biological networks.
  • The web server facilitates advanced drug discovery through deep learning on HINs, making complex analyses available to researchers.
  • DRHIN is freely accessible at http://drhin.tianshanzw.cn, promoting wider adoption and reproducibility in the field.