目的 探究近10年藥物相互作用（DDI）領(lǐng)域預(yù)測(cè)模型的研究現(xiàn)狀和熱點(diǎn)。方法 檢索2013年1月1日—2024年8月13日Web of Science核心合集數(shù)據(jù)庫(kù)中發(fā)表的有關(guān)DDI預(yù)測(cè)模型研究文獻(xiàn)，運(yùn)用CiteSpace 6.3 R1軟件繪制作者、研究機(jī)構(gòu)、國(guó)家地區(qū)合作網(wǎng)絡(luò)以及期刊、關(guān)鍵詞可視化知識(shí)圖譜，進(jìn)行文獻(xiàn)計(jì)量分析。結(jié)果 2013—2024年DDI預(yù)測(cè)模型研究相關(guān)文獻(xiàn)754篇，發(fā)文量呈逐年上升趨勢(shì)；美國(guó)發(fā)文量最多，中國(guó)其次；發(fā)文量最多的學(xué)者是Sugiyama，Yuichi；發(fā)文量第1的研究機(jī)構(gòu)是RLUK-Research Libraries UK；熱點(diǎn)關(guān)鍵詞為抑制、代謝、藥代動(dòng)力學(xué)、清除率；發(fā)文量最多的期刊及被引頻次最高的期刊是Bioinformatics；在高頻被引文獻(xiàn)中顯示了對(duì)機(jī)器學(xué)習(xí)、深度學(xué)習(xí)的關(guān)注度較高。結(jié)論 分析2013—2024年DDI預(yù)測(cè)模型文獻(xiàn)，可知此領(lǐng)域研究熱點(diǎn)為藥動(dòng)學(xué)和體外實(shí)驗(yàn)研究，研究前沿為機(jī)器學(xué)習(xí)和深度學(xué)習(xí)，為未來(lái)研究提供新的視角。

Objective To explore the research status and hotspots of drug-drug interactions (DDI) prediction model in the last 10 years. Methods The relevant English literature on DDI prediction model published from 2013 to 2024 was retrieved from Web of Science (WOS) database. CiteSpace software was used to visual analysis. Results A total of 754 pieces of paper related to DDI prediction model were obtained, and the number of publications showed an increasing trend. The country with the most articles was the United States, followed by China. The person who published the most articles was Dr. Yuichi Sugiyama. The research institution with the largest number of publications was RLUK-Research Libraries UK. Hot keywords were inhibition, metabolism, pharmacokinetics, clearance. The journal with the highest number of publications and the most frequently cited journal was Bioinformatics. Machine learning and deep learning are gotten high attention by the high frequency cited literature. Conclusion CiteSpace software was used to analyze the literature on DDI prediction models, and it was found that in vitro experimental studies, pharmacokinetics, machine learning and deep learning are the research frontiers in this field, providing a new perspective for the study of DDI prediction models.

R969.2

中國(guó)藥品監(jiān)督管理研究會(huì)研究課題-基于多元證據(jù)體探索中成藥安全性評(píng)價(jià)方法的研究(2024-Y-Y-006)；臨床研究和成果轉(zhuǎn)化能力提升試點(diǎn)項(xiàng)目-中藥制劑研發(fā)——治療胃輕癱中藥復(fù)方佛香散(DZMG-ZJXY-23002)