Will AI Bring New Medicines Against Heart Disease?

被引:0
作者
Glaser, Manuel [1 ]
Ritterhof, Julia [2 ,3 ]
Most, Patrick [2 ,3 ,4 ]
Wade, Rebecca C. [1 ,5 ,6 ,7 ]
机构
[1] Heidelberg Inst Theoret Studies HITS, Mol & Cellular Modeling Grp, Heidelberg, Germany
[2] Heidelberg Univ Hosp, Mol & Translat Cardiol, Heidelberg, Germany
[3] Heidelberg Univ Hosp, Dept Cardiol Angiol & Pneumol, Heidelberg, Germany
[4] Thomas Jefferson Univ, Ctr Translat Med, Philadelphia, PA USA
[5] Heidelberg Univ, Univ Heidelberg ZMBH, DKFZ ZMBH Alliance, Zent Molekulare Biol, D-69120 Heidelberg, Germany
[6] Heidelberg Univ, Interdisciplinary Ctr Sci Comp IWR, Heidelberg, Germany
[7] Heidelberg Inst Theoret Studies HITS, Mol & Cellular Modeling Grp, Schloss Wolfsbrunnenweg 35, D-69118 Heidelberg, Germany
关键词
machine learning; molecular simulation; drug design; drug discovery; drug development; artificial intelligence (AI);
D O I
10.1055/a-2131-2843
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Given the transformational impact that artificial intelligence (AI) is having on science, medicine and beyond, we here consider the potential of AI for the discovery of new medicines against heart disease. We define AI broadly as the use of machine learning, including statistics and deep learning, to identify patterns in datasets that can be used to make predictions. Recent breakthroughs in the ability to consider very large amounts of data have spurred a boom in AI-driven drug discovery in both academia and industry. Many new companies already have drug pipelines extending into clinical trials, but these do not yet include drugs against heart disease. We here describe the use of AI for the discovery of low-molecular weight drugs and biologics, including therapeutic peptides, as well as for predicting effects such as cardiotoxicity. The concerted use of AI together with physics-based simulations and experimental feedback loops will be necessary to fully realize the potential of AI for drug discovery and the development of precision medicines for cardiac conditions.
引用
收藏
页码:450 / 458
页数:9
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