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通过区块链和生成式人工智能实现生物样本库的明确同意。

Enabling Demonstrated Consent for Biobanking with Blockchain and Generative AI.

作者信息

Barnes Caspar, Aboy Mateo Riobo, Minssen Timo, Allen Jemima Winifred, Earp Brian D, Savulescu Julian, Mann Sebastian Porsdam

机构信息

Harvard Medical School.

AminoChain, Inc.

出版信息

Am J Bioeth. 2025 Apr;25(4):96-111. doi: 10.1080/15265161.2024.2416117. Epub 2024 Nov 5.

Abstract

Participation in research is supposed to be voluntary and informed. Yet it is difficult to ensure people are adequately informed about the potential uses of their biological materials when they donate samples for future research. We propose a novel consent framework which we call "demonstrated consent" that leverages blockchain technology and generative AI to address this problem. In a demonstrated consent model, each donated sample is associated with a unique non-fungible token (NFT) on a blockchain, which records in its metadata information about the planned and past uses of the sample in research, and is updated with each use of the sample. This information is accessible to a large language model (LLM) customized to present this information in an understandable and interactive manner. Thus, our model uses blockchain and generative AI technologies to track, make available, and explain information regarding planned and past uses of donated samples.

摘要

参与研究应该是自愿且基于充分知情的。然而,当人们为未来研究捐赠样本时,很难确保他们充分了解其生物材料的潜在用途。我们提出了一种新颖的同意框架,我们称之为“示范同意”,它利用区块链技术和生成式人工智能来解决这个问题。在示范同意模型中,每个捐赠的样本在区块链上都与一个独特的非同质化代币(NFT)相关联,该代币在其元数据中记录样本在研究中的计划用途和过往用途信息,并在每次样本使用时进行更新。一个经过定制的大语言模型(LLM)可以访问这些信息,该模型能够以易懂且互动的方式呈现这些信息。因此,我们的模型利用区块链和生成式人工智能技术来跟踪、提供并解释有关捐赠样本计划用途和过往用途的信息。

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