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人工智能将再生医学带入预测领域。

Artificial intelligence powers regenerative medicine into predictive realm.

作者信息

Garmany Armin, Terzic Andre

机构信息

Marriott Heart Disease Research Program, Department of Cardiovascular Medicine, Department of Molecular Pharmacology & Experimental Therapeutics, Department of Clinical Genomics, Mayo Clinic, Rochester, MN, USA.

Mayo Clinic Alix School of Medicine, Regenerative Sciences Track, Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN, USA.

出版信息

Regen Med. 2024 Dec;19(12):611-616. doi: 10.1080/17460751.2024.2437281. Epub 2024 Dec 11.

Abstract

The expanding regenerative medicine toolkit is reaching a record number of lives. There is a pressing need to enhance the precision, efficiency, and effectiveness of regenerative approaches and achieve reliable outcomes. While regenerative medicine has relied on an empiric paradigm, availability of big data along with advances in informatics and artificial intelligence offer the opportunity to inform the next generation of regenerative sciences along the discovery, translation, and application pathway. Artificial intelligence can streamline discovery and development of optimized biotherapeutics by aiding in the interpretation of readouts associated with optimal repair outcomes. In advanced biomanufacturing, artificial intelligence holds potential in ensuring quality control and assuring scalability through automated monitoring of process-critical variables mandatory for product consistency. In practice application, artificial intelligence can guide clinical trial design, patient selection, delivery strategies, and outcome assessment. As artificial intelligence transforms the regenerative horizon, caution is necessary to reduce bias, ensure generalizability, and mitigate ethical concerns with the goal of equitable access for patients and populations.

摘要

不断扩展的再生医学工具包正在影响着创纪录数量的生命。迫切需要提高再生方法的精准性、效率和有效性,并实现可靠的结果。虽然再生医学一直依赖于经验范式,但大数据的可用性以及信息学和人工智能的进步为在发现、转化和应用途径上为下一代再生科学提供信息创造了机会。人工智能可以通过帮助解读与最佳修复结果相关的读数,简化优化生物疗法的发现和开发。在先进的生物制造中,人工智能在通过对确保产品一致性所需的关键工艺变量进行自动监测来保证质量控制和可扩展性方面具有潜力。在实际应用中,人工智能可以指导临床试验设计、患者选择、给药策略和结果评估。随着人工智能改变再生医学的前景,必须谨慎行事,以减少偏差、确保普遍性并减轻伦理问题,目标是让患者和人群能够公平获得治疗。

相似文献

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Artificial intelligence powers regenerative medicine into predictive realm.人工智能将再生医学带入预测领域。
Regen Med. 2024 Dec;19(12):611-616. doi: 10.1080/17460751.2024.2437281. Epub 2024 Dec 11.
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Machine learning in preclinical drug discovery.机器学习在临床前药物发现中的应用。
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