CRISPR基因编辑技术风险画像标签体系构建研究

Research on the Construction of a Risk Profile Label System for CRISPR Gene Editing Technology

摘要: 本文提出了一种CRISPR基因编辑技术风险画像标签体系，旨在系统识别和量化该技术在扩散过程中可能带来的多维风险。传统风险研究方法存在滞后性和碎片化问题，难以动态捕捉人员、工具、物种等关键风险要素之间的复杂互动关系。为此，本文构建了一个包含物种可编辑性风险和工具编辑能力风险的双层标签体系，每个一级标签下设三个二级标签，分别从能力、工具覆盖度和人员覆盖度三个维度进行刻画。研究进一步提出了包括工作总数、物种流行度、工具流行度等在内的六个量化指标，并引入一元线性回归模型对未来风险趋势进行预测。通过一个基于文献抽取数据的示例，文章展示了标签体系的具体计算流程与应用效果，验证了该方法的客观性、前瞻性与全面性。该研究为CRISPR技术的风险治理提供了新的量化工具与预警机制支持。

Abstract: This paper proposes a risk profile label system for CRISPR gene editing technology, aiming to systematically identify and quantify the multi-dimensional risks that may arise during its diffusion. Traditional risk research methods suffer from issues of lag and fragmentation, making it difficult to dynamically capture the complex interactions among key risk elements such as personnel, tools, and species. To address this, this study constructs a two-tier label system comprising species editability risk and tool editing capability risk. Each first-level label contains three second-level labels, characterized across three dimensions: capability, tool coverage, and personnel coverage. The research further introduces six quantitative indicators, including the total number of research efforts, species popularity, and tool popularity, and employs a univariate linear regression model to predict future risk trends. Through an example based on data extracted from the literature, the paper demonstrates the specific calculation process and application effectiveness of the label system, verifying the method’s objectivity, foresight, and comprehensiveness. This research provides a new quantitative tool and early warning mechanism for the risk governance of CRISPR technology.