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Biguanides, particularly metformin (Glucophage), are insulin sensitizers that enhance glucose uptake, thereby reducing insulin resistance. Unlike sulfonylureas, metformin doesn't prompt insulin secretion, which helps to curb hypoglycemia risk. Metformin is beneficial in treating conditions like polycystic ovary syndrome due to its insulin-resistance reduction capability. The drug's primary action involves curtailing hepatic gluconeogenesis, a significant contributor to high blood...
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Repaglinide (Prandin) and Nateglinide (Starlix), known as glinides, are oral insulin secretagogues that stimulate insulin release from pancreatic β cells by closing the ATP-sensitive potassium channels (KATP channel). Repaglinide controls insulin release from pancreatic β cells by managing potassium efflux. It shares two binding sites with sulfonylureas and also has a unique site, indicating overlapping mechanisms of action. With a rapid onset and a 4-7 hour duration, it effectively...
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Diabetes: Management and Pharmacotherapy01:15

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The therapy for diabetes aims to alleviate hyperglycemia-related symptoms, prevent acute metabolic decompensation, and reduce chronic end-organ complications. Glycemic control is evaluated through short-term (self-monitoring, continuous glucose monitoring) and long-term (A1c, fructosamine) metrics, enabling near real-time tracking of blood glucose levels and reflecting glycemic control over specific time frames.
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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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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
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Modern computational intelligence based drug repurposing for diabetes epidemic.

Sweta Mohanty1, Md Harun Al Rashid2, Chandana Mohanty1

  • 1School of Applied Science, KIIT University, Bhubaneswar, Odisha, India.

Diabetes & Metabolic Syndrome
|June 29, 2021
PubMed
Summary

This study explores new antidiabetic agents discovered through drug repurposing and highlights technologies for diabetes drug discovery. Artificial intelligence integration with pharmacology can significantly enhance drug repurposing efficiency for diabetes treatment.

Keywords:
Artificial intelligenceDiabetesDrug repurposingModern computational intelligence modelsMolecular property diagnostic suite diabetes mellitus (MPDSDM)

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Area of Science:

  • Pharmacology
  • Drug Discovery
  • Computational Biology

Background:

  • Diabetes mellitus is a growing global health concern requiring novel therapeutic strategies.
  • Traditional drug discovery is time-consuming and expensive, necessitating alternative approaches.
  • Drug repurposing offers a faster and more cost-effective route to identify new antidiabetic agents.

Purpose of the Study:

  • To review recent advancements in discovering antidiabetic agents via drug repurposing.
  • To discuss modern technologies facilitating drug repurposing, including specialized web portals for diabetes.
  • To identify potential drug candidates for diabetes treatment through repurposing strategies.

Main Methods:

  • Comprehensive literature review of scientific databases (Scopus, PubMed, IEEE Xplore).
  • Analysis of existing drugs for potential repurposing against diabetes.
  • Exploration of technological tools and platforms supporting drug repurposing.

Main Results:

  • Several drugs, including Niclosamideethanolamine, Methazolamide, Diacerein, Berberine, and Clobetasol, show promise for repurposing as antidiabetic agents.
  • These candidates offer potential late-stage clinical development pathways.
  • Information on pharmacology, formulation, and toxicity is crucial for evaluating repurposed drugs.

Conclusions:

  • Drug repurposing, aided by modern technologies, accelerates the discovery of novel antidiabetic therapies.
  • Artificial intelligence (AI) combined with pharmacology can significantly improve the efficiency and success rate of drug repurposing.
  • Further research and development are warranted to bring these potential candidates to clinical application.