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相关概念视频

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

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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
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
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Drug Administration and Therapy Phases: Overview01:26

Drug Administration and Therapy Phases: Overview

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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.
The pharmaceutical phase focuses on leveraging the physicochemical properties of the drug to design and manufacture an effective product. Variants include orally administered tablets or capsules, topical creams or ointments, and parenteral-delivery solutions or emulsions.
The pharmacokinetic phase...
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Biopharmaceutics and Pharmacokinetics: Overview01:28

Biopharmaceutics and Pharmacokinetics: Overview

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Understanding drugs, drug products, and their performance in pharmaceutical science is pivotal. Drugs, whether simple molecules or complex compounds, are designed to interact with the body's biological systems to diagnose, treat, or prevent diseases. Drug products include various delivery systems such as tablets, capsules, injections, and inhalers. The performance of these drug products is gauged by their ability to deliver the active ingredient to the desired site of action at the...
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Structure-Activity Relationships and Drug Design01:28

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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.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
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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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Preclinical Development: Overview01:28

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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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相关实验视频

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Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
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一项全面的调查:通过人工智能发展制药行业

Deepak Jain1, Phool Chandra2, Zeeshan Ali3

  • 1Research Scholar, Department of Pharmaceutics, School of Pharmacy- AVIPS, Shobit University, Gangoh, Uttar Pradesh, 247341, India.

Current drug discovery technologies
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概括

人工智能 (AI) 正在通过提高疾病检测,药物发现和临床试验效率来彻底改变制药行业. 人工智能集成提高了生产率,降低了成本,改变了制药研究和开发.

关键词:
人工智能的人工智能是人工智能.发展和发展和发展和发展.剂量监测 剂量监测 剂量监测药物开发和发现.医学诊断 医学诊断 医学诊断神经系统疾病.神经系统疾病.研究的研究研究的研究.

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科学领域:

  • 制药科学 制药科学
  • 生物技术是生物技术.
  • 计算生物学 计算生物学

背景情况:

  • 人工智能 (AI) 正在越来越多地影响各种行业,包括制药行业.
  • 制药行业在药物发现,临床试验和运营效率方面面临着挑战.

研究的目的:

  • 审查AI在制药行业的多方面的好处.
  • 突出AI在疾病检测,药物开发,临床试验和整体生产力方面的作用.

主要方法:

  • 在制药研究和开发中对人工智能应用进行系统审查.
  • 分析AI在机器学习中的使用,用于数据分析和模式识别.
  • 检查AI在提高诊断准确性和药物补救方面的作用.

主要成果:

  • 人工智能显著改善了疾病检测,临床试验患者识别和抗病毒疗效.
  • 人工智能通过分析大量数据集和预测药物的疗效来加速药物发现和开发.
  • 人工智能提高了运营效率,降低了成本,并为市场表现和用户行为提供了洞察力.

结论:

  • 人工智能集成正在改变医药研发,从药物发现和诊断到制造和营销.
  • 人工智能能够更准确地分析数据,从而开发出有效和经济高效的疗法.
  • 制药公司正在利用人工智能进行预测建模,神经评估和疾病诊断,展示其广泛的适用性.