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Related Concept Videos

Drug Discovery: Overview01:26

Drug Discovery: Overview

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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 design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
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Drug Administration and Therapy Phases: Overview01:26

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Drugs, the chemical agents used in diagnosing, treating, or preventing diseases, undergo a four-phase process of development: pharmaceutic, pharmacokinetics, pharmacodynamics, and therapeutic.
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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
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Principles of Drug Action01:24

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Drugs are chemical substances that modify biological responses by interacting with macromolecular targets such as receptors, ion channels, transporters, and enzymes. Pharmacodynamics describes the course of action of drugs leading to the physiological effect at a specific site in the body.
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Preclinical development consists of a series of tests that ensure the safety and efficacy of a new therapeutic compound before it is tested in humans. There are four main phases to this process. First, safety pharmacology tests are conducted to ensure the drug does not produce any acutely harmful effects. These tests examine parameters such as bronchoconstriction, cardiac dysrhythmias, blood pressure changes, and ataxia. Next, preliminary toxicological testing is performed to determine the...
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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
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Artificial Intelligence Effecting a Paradigm Shift in Drug Development.

Masturah Bte Mohd Abdul Rashid1

  • 1KYAN Therapeutics, Singapore, Singapore.

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|September 17, 2020
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Summary
This summary is machine-generated.

Artificial intelligence (AI) streamlines drug development, reducing costs and improving clinical trial success. AI applications in target identification, repositioning, and patient stratification pave the way for precision medicine.

Keywords:
artificial intelligencedrug developmentdrug discoveryindustry

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Area of Science:

  • Pharmacology
  • Computational Biology
  • Biotechnology

Background:

  • High drug development costs and low market integration necessitate innovative solutions.
  • Premature clinical trial termination and regulatory hurdles impede drug development success.

Purpose of the Study:

  • To review and compare artificial intelligence (AI) applications in drug development.
  • To highlight AI's role in automating processes and improving success rates.
  • To explore AI's translation into clinical practice for precision medicine.

Main Methods:

  • Literature review of AI applications in drug discovery and development.
  • Comparison of AI tools for novel drug target identification and design.
  • Analysis of AI in drug repositioning, biomarker identification, and patient stratification.

Main Results:

  • AI accelerates and enhances drug development, leading to more efficient processes.
  • AI improves success rates in clinical trials through better target identification and patient stratification.
  • AI facilitates the integration of precision and personalized medicine.

Conclusions:

  • AI is revolutionizing drug development by automating key processes and reducing costs.
  • AI-driven approaches enhance the probability of successful drug integration into the market.
  • The continued advancement of AI promises greater achievements in personalized medicine.