人工智能如何使生物网络建模和模拟加速药物发现

M. DiNuzzo
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引用次数: 0

摘要

制药行业在过去的几十年里遭受了创新的显著下降,其简单的原因是复杂的生物学。人工智能(AI)有望使整个药物发现和开发过程更加高效。在这里,我考虑了使用人工智能的潜在好处,通过利用数据和知识来建模和模拟基因组尺度的生物网络,加深我们对疾病的机制理解。我概述了推动该领域向前发展的最新发展,并确定了将人工智能与药物发现中的建模和仿真成功整合在一起的几个主要挑战。
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How artificial intelligence enables modeling and simulation of biological networks to accelerate drug discovery
The pharmaceutical industry suffered a significant decline of innovation in the last few decades, whose simple reason is complex biology. Artificial intelligence (AI) promises to make the entire drug discovery and development process more efficient. Here I consider the potential benefits of using AI to deepen our mechanistic understanding of disease by leveraging data and knowledge for modeling and simulation of genome-scale biological networks. I outline recent developments that are moving the field forward and I identify several overarching challenges for advancing the state of the art towards the successful integration of AI with modeling and simulation in drug discovery.
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