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Related Concept Videos

Combined Effects of Drugs: Synergism01:27

Combined Effects of Drugs: Synergism

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Synergism is a useful mechanism where combining two or more drugs is more effective than each constituent used alone. Such combinations are also called supra-additive interactions. The drugs collectively enhance the final therapeutic effect by acting on different targets. Another advantage is that the low dose of each constituent drug is sufficient to achieve the desired effect. This helps reduce the duration of therapy and lower the adverse effects of these drugs.
Such synergistic combinations...
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During the development of a new pharmaceutical, the manufacturer initially assigns a code name to the drug. Once approved, the drug receives a United States Adopted Name (USAN)—a generic, nonproprietary designation. Upon being listed in the United States Pharmacopeia, this nonproprietary name becomes the drug's official name. Additionally, the manufacturer assigns a proprietary name or trademark, which serves as the brand name under which the drug is marketed. It is worth noting that...
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Drug Dosage Regimen: Overview01:15

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A drug dosage regimen describes the specific instructions and schedule for administering a drug to a patient. It considers factors such as drug dosage, frequency, route of administration, and duration of treatment. Designing an appropriate dosage regimen for a patient aims to achieve a target drug concentration at the site of action.
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Drug Discovery: Overview01:26

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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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Combined Effects of Drugs: Antagonism01:30

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The combined effects of drugs can result in various interactions, of which an important type is antagonism. Antagonism is a mechanism where one drug inhibits or counteracts the effects of another drug. Antagonism can occur through various means, including receptor binding, allosteric modulation, functional interaction, chemical reactions, and pharmacokinetic processes.
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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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Updated: Sep 21, 2025

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
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CDCDB: A large and continuously updated drug combination database.

Guy Shtar1, Louise Azulay2, Omer Nizri3

  • 1Ben-Gurion University of the Negev, Department of Software and Information Systems Engineering, Beer-Sheva, 8410501, Israel. shtar@post.bgu.ac.il.

Scientific Data
|June 2, 2022
PubMed
Summary
This summary is machine-generated.

The Continuous Drug Combination Database (CDCDB) streamlines drug discovery by providing a continuously updated resource. It aids in identifying effective drug combinations for complex diseases and bacterial infections, moving beyond static data limitations.

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Area of Science:

  • Computational biology
  • Pharmacology
  • Bioinformatics

Background:

  • The multiple-drugs for multiple-targets paradigm is gaining traction for treating complex diseases and bacterial infections due to the synergistic effects of drug combinations.
  • Experimental high-throughput screening for novel drug combinations is limited by the vast number of potential combinations.
  • Existing drug combination databases are static, hindering their utility for dynamic computational models.

Purpose of the Study:

  • To introduce the Continuous Drug Combination Database (CDCDB), a novel, continuously updated resource for drug combination data.
  • To facilitate streamlined drug combination screening and prediction through computational methods.
  • To support the development of predictive models for drug synergy.

Main Methods:

  • Curated data from ClinicalTrials.gov, FDA Orange Book®, and patents.
  • Utilized natural language processing (NLP) techniques for efficient data extraction and integration.
  • Developed a continuously updated database architecture to overcome limitations of static datasets.

Main Results:

  • The CDCDB contains over 40,795 drug combinations, including 17,107 unique combinations involving more than 4,129 individual drugs.
  • The database is designed for continuous updates, ensuring relevance and comprehensiveness.
  • The curated data and NLP methods enhance drug combination discovery processes.

Conclusions:

  • The CDCDB represents a significant advancement in drug combination research by offering a dynamic and comprehensive data resource.
  • This continuously updated database is crucial for advancing computational drug discovery and synergy prediction.
  • CDCDB supports the paradigm shift towards multi-drug, multi-target therapies for complex health challenges.