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在精准肿瘤学中,基于人工智能的个性化药物和细胞疗法需要新的监管思路。

New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology.

作者信息

Derraz Bouchra, Breda Gabriele, Kaempf Christoph, Baenke Franziska, Cotte Fabienne, Reiche Kristin, Köhl Ulrike, Kather Jakob Nikolas, Eskenazy Deborah, Gilbert Stephen

机构信息

ProductLife Group, Paris, France.

Groupe de recherche et d'accueil en droit et économie de la santé (GRADES), Faculty of Pharmacy, University Paris-Saclay, Paris, France.

出版信息

NPJ Precis Oncol. 2024 Jan 30;8(1):23. doi: 10.1038/s41698-024-00517-w.


DOI:10.1038/s41698-024-00517-w
PMID:38291217
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10828509/
Abstract

Until recently the application of artificial intelligence (AI) in precision oncology was confined to activities in drug development and had limited impact on the personalisation of therapy. Now, a number of approaches have been proposed for the personalisation of drug and cell therapies with AI applied to therapy design, planning and delivery at the patient's bedside. Some drug and cell-based therapies are already tuneable to the individual to optimise efficacy, to reduce toxicity, to adapt the dosing regime, to design combination therapy approaches and, preclinically, even to personalise the receptor design of cell therapies. Developments in AI-based healthcare are accelerating through the adoption of foundation models, and generalist medical AI models have been proposed. The application of these approaches in therapy design is already being explored and realistic short-term advances include the application to the personalised design and delivery of drugs and cell therapies. With this pace of development, the limiting step to adoption will likely be the capacity and appropriateness of regulatory frameworks. This article explores emerging concepts and new ideas for the regulation of AI-enabled personalised cancer therapies in the context of existing and in development governance frameworks.

摘要

直到最近,人工智能(AI)在精准肿瘤学中的应用还局限于药物研发活动,对治疗的个性化影响有限。现在,已经提出了一些利用人工智能进行药物和细胞治疗个性化的方法,将其应用于床边患者的治疗设计、规划和实施。一些基于药物和细胞的疗法已经可以根据个体情况进行调整,以优化疗效、降低毒性、调整给药方案、设计联合治疗方法,甚至在临床前就可以对细胞疗法的受体设计进行个性化。基于人工智能的医疗保健发展正在通过采用基础模型加速推进,并且已经提出了通用医学人工智能模型。这些方法在治疗设计中的应用已经在探索中,现实的短期进展包括应用于药物和细胞疗法的个性化设计和实施。随着这种发展速度,采用的限制步骤可能是监管框架的能力和适用性。本文探讨了在现有和正在发展的治理框架背景下,对人工智能驱动的个性化癌症治疗进行监管的新兴概念和新想法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d07/10828509/e348d230549d/41698_2024_517_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d07/10828509/af6a4ccf5bbe/41698_2024_517_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d07/10828509/e348d230549d/41698_2024_517_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d07/10828509/af6a4ccf5bbe/41698_2024_517_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d07/10828509/e348d230549d/41698_2024_517_Fig2_HTML.jpg

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本文引用的文献

[1]
How AI can learn from the law: putting humans in the loop only on appeal.

NPJ Digit Med. 2023-8-25

[2]
The shaky foundations of large language models and foundation models for electronic health records.

NPJ Digit Med. 2023-7-29

[3]
Prediction of lymphoma response to CAR T cells by deep learning-based image analysis.

PLoS One. 2023

[4]
Large language models encode clinical knowledge.

Nature. 2023-8

[5]
The imperative for regulatory oversight of large language models (or generative AI) in healthcare.

NPJ Digit Med. 2023-7-6

[6]
Pearls and pitfalls of ChatGPT in medical oncology.

Trends Cancer. 2023-10

[7]
Large language model AI chatbots require approval as medical devices.

Nat Med. 2023-10

[8]
Artificial Intelligence in Molecular Medicine.

N Engl J Med. 2023-6-29

[9]
Multi-cancer early detection test in symptomatic patients referred for cancer investigation in England and Wales (SYMPLIFY): a large-scale, observational cohort study.

Lancet Oncol. 2023-7

[10]
Bias in AI-based models for medical applications: challenges and mitigation strategies.

NPJ Digit Med. 2023-6-14

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