Department of Pharmacotherapy and Pharmaceutics (DPP), Université Libre de Bruxelles (ULB), Boulevard du Triomphe, CP 205/07, Access 2, Campus de la Plaine, Building BC, 1050, Bruxelles, Belgium.
Machine Learning Group, Université Libre de Bruxelles (ULB), Bruxelles, Belgium.
Clin Pharmacokinet. 2022 Jun;61(6):761-788. doi: 10.1007/s40262-022-01131-4. Epub 2022 May 31.
Herbal food supplements are commonly used and can be an important part of patient self-care. Like all other bio-active and therapeutic products, they have a benefit/risk balance. These products are not without adverse effects and potentially interact with other therapies. Educating patients and providing information for health professionals about the risk of herb-drug interactions is key. One of the purposes of the biomedical literature is to inform prescribers. Scientific literature accessible on databases such as PubMed is dense and careful reading is time consuming. We propose a reading aid tool named "HDI highlighter" to help readers to find key information in clinical studies and case reports describing herb-drug interactions. It uses natural language processing algorithms (artificial intelligence) with a pharmaceutical focus. Semantic relation extraction for herb-drug interactions from the biomedical literature are overexpressed using keywords. We have tested it to review 120 published articles over the last 10 years. In these articles, we have shown that case reports often involved long-term or semi-long-term treatments such as cancer or human immunodeficiency virus therapies, antiepileptic drugs, or central nervous system drugs. Similarly, these classes of drugs are more extensively targeted by clinical studies. Herb-drug interactions described in case reports are identified in medicinal, recreational, and alimentary uses. They also usually lack a rigorous description of the herb(s) involved. Typically, clinical studies provide a complete description of protocols and dosages, with a few exceptions explained by patients' needs. Clinical studies on herbs are nevertheless conducted on a limited number of patients. All these limitations make the interpretation of herb-drug interactions complicated, but the HDI highlighter provides a quick overview of the herb-drug interaction literature.
草药食品补充剂通常被使用,并且可以成为患者自我护理的重要组成部分。与所有其他生物活性和治疗产品一样,它们具有获益/风险平衡。这些产品并非没有不良反应,并且可能与其他疗法相互作用。向患者提供教育,并向卫生专业人员提供有关草药-药物相互作用风险的信息是关键。生物医学文献的目的之一是为开处方者提供信息。可以在 PubMed 等数据库中访问的科学文献密度很高,仔细阅读需要时间。我们提出了一种名为“HDIHighlight 工具”的阅读辅助工具,以帮助读者在描述草药-药物相互作用的临床研究和病例报告中找到关键信息。它使用专注于药物的自然语言处理算法(人工智能)。使用关键字从生物医学文献中提取草药-药物相互作用的语义关系。我们已经对其进行了测试,以审查过去 10 年中发表的 120 篇文章。在这些文章中,我们表明病例报告通常涉及长期或半长期治疗,如癌症或人类免疫缺陷病毒治疗、抗癫痫药物或中枢神经系统药物。同样,这些类别的药物在临床研究中更广泛地受到关注。病例报告中描述的草药-药物相互作用在药用、娱乐和饮食用途中都有涉及。它们通常也缺乏对所涉及草药的严格描述。通常,临床研究提供了协议和剂量的完整描述,只有少数例外是由患者的需求解释的。然而,对草药的临床研究仅在有限数量的患者中进行。所有这些限制使得草药-药物相互作用的解释变得复杂,但是 HDIHighlight 工具提供了草药-药物相互作用文献的快速概述。