[目的/意义] 构建一个引擎技术预见模型（ITFM），可用于预见引擎技术。[方法/过程] 该模型包含四类指标：技术生命周期（专利演化）、国际环境、合作（专利权人合作网络）和影响力。通过专家咨询选择生命科学领域的四个技术用于验证分析，并对ITFM模型进行量化，其中DNA重组技术（RbDNA）和单克隆抗体技术（mAb）作为引擎技术，发酵技术（FT）和ELISA诊断技术（ELISA）作为非引擎技术对照组。[结果/结论] 引擎技术进入成熟期后专利数量稳定在一定的水平；重大政策、计划和规划往往会推动引擎技术的快速发展；引擎技术的专利合作程度更高；引擎技术的专利件均被引频次更高。合成生物学技术（SynBio）被用于开展实证分析，实证分析表明，ITFM模型可揭示出合成生物学技术尚处于发展的成长期，具有演化为引擎技术的潜力。
[Purpose/significance] This paper constructs an Impelling Technology Foresight Model (ITFM) used for foreseeing impelling technologies in the field of life science. [Method/process] ITFM is a comprehensive model consisting of four classes of indicators: international scientific environment, the evolving process of patents, collaboration features of patent assignees collaboration networks, and impacts. A validating study was carried out in the field of life science. Recombinant DNA (RbDNA) and Monoclonal Antibody (mAb) were selected as impelling technologies to carry out a validating study. ELISA Diagnosis (ELISA) and Fermentation Technology (FT) were defined as non-impelling technologies to be a control group. [Result/conclusion] Validating results reveal that the patent number of impelling technologies seems to be stable at the stage of maturity. Significant policies or programs usually boost the rapid progress of impelling technologies. Impelling technologies have much higher impact than non-impelling technologies. Collaboration behavior of impelling technologies is much more broad and general. Synthetic Biology (SynBio) is used to carry out the case study to foresee whether it could become impelling technology or not. The case study shows that SynBio might be at the early stage of development. It has shown some features of impelling technologies and has a prospect of becoming impelling technologies.
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