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引用次数: 0
摘要
药物发现是一个复杂而多面的过程,旨在找出有可能治疗各种疾病的新治疗化合物。传统的药物发现方法往往耗时长、成本高、成功率低。因此,迫切需要利用新技术改进药物开发过程。将当前最先进的人工智能(AI)和机器学习(ML)方法与传统方法相结合,将提高药物研究的效率和效果。本综述强调了人工智能和 ML 对药物发现的变革性影响,讨论了利用这些技术加快创新疗法开发的当前应用、挑战和未来方向。我们讨论了人工智能和 ML 技术的最新发展,以简化药物发现的几个阶段,从靶点识别和验证到先导优化和临床前研究。
Unleashing the future: The revolutionary role of machine learning and artificial intelligence in drug discovery
Drug discovery is a complex and multifaceted process aimed at identifying new therapeutic compounds with the potential to treat various diseases. Traditional methods of drug discovery are often time-consuming, expensive, and characterized by low success rates. Because of this, there is an urgent need to improve the drug development process using new technologies. The integration of the current state-of-art of artificial intelligence (AI) and machine learning (ML) approaches with conventional methods will enhance the efficiency and effectiveness of pharmaceutical research. This review highlights the transformative impact of AI and ML in drug discovery, discussing current applications, challenges, and future directions in harnessing these technologies to accelerate the development of innovative therapeutics. We have discussed the latest developments in AI and ML technologies to streamline several stages of drug discovery, from target identification and validation to lead optimization and preclinical studies.
期刊介绍:
The European Journal of Pharmacology publishes research papers covering all aspects of experimental pharmacology with focus on the mechanism of action of structurally identified compounds affecting biological systems.
The scope includes:
Behavioural pharmacology
Neuropharmacology and analgesia
Cardiovascular pharmacology
Pulmonary, gastrointestinal and urogenital pharmacology
Endocrine pharmacology
Immunopharmacology and inflammation
Molecular and cellular pharmacology
Regenerative pharmacology
Biologicals and biotherapeutics
Translational pharmacology
Nutriceutical pharmacology.