分子大数据、机器智能和个性化健康时代的药食交互作用。

Romy Roy, Shamsudheen Marakkar, Munawar Peringadi Vayalil, Alisha Shahanaz, Athira Panicker Anil, Shameer Kunnathpeedikayil, Ishaan Rawal, Kavya Shetty, Zahrah Shameer, Saraswathi Sathees, Adarsh Pooradan Prasannakumar, Oommen Kaleeckal Mathew, Lakshminarayanan Subramanian, Khader Shameer, Kamlesh K Yadav
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引用次数: 0

摘要

药物与食物的相互作用会改变药物的临床效果。有利的相互作用会带来积极的临床结果,而不利的相互作用则可能导致药物毒性。本文回顾了食物摄入对药物-食物相互作用的影响、药物的临床效应以及药物-食物与饮食和精准医疗的相关效应。药物与食物相互作用的新兴领域是食物基因组界面(营养基因组学)和营养遗传学。了解食品成分的分子基础,包括基因组测序和食品分子的药理作用,有助于减少药食相互作用的影响。目前正在利用各种策略来减轻药物与食品之间的相互作用,其中包括患者参与、数字健康、涉及机器智能的方法和大数据等措施。此外,在药物微生物组框架内描述膳食微生物组-药物-食物-药物相互作用的分子沟通也可能在个性化营养方面发挥重要作用。确定营养素与基因之间的相互作用有助于实现深度个性化营养,并有助于从一开始就减轻不必要的药物-食物相互作用、慢性疾病和不良事件。转化生物信息学方法可在下一代药物-食物相互作用研究中发挥重要作用。在这篇综述中,我们将讨论重要的工具、数据库和方法,以及药物-食物相互作用的关键挑战和机遇及其对精准医学的直接影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Drug-food Interactions in the Era of Molecular Big Data, Machine Intelligence, and Personalized Health.

Drug-food Interactions in the Era of Molecular Big Data, Machine Intelligence, and Personalized Health.

Drug-food Interactions in the Era of Molecular Big Data, Machine Intelligence, and Personalized Health.

Drug-food Interactions in the Era of Molecular Big Data, Machine Intelligence, and Personalized Health.

The drug-food interaction brings forth changes in the clinical effects of drugs. While favourable interactions bring positive clinical outcomes, unfavourable interactions may lead to toxicity. This article reviews the impact of food intake on drug-food interactions, the clinical effects of drugs, and the effect of drug-food in correlation with diet and precision medicine. Emerging areas in drug-food interactions are the food-genome interface (nutrigenomics) and nutrigenetics. Understanding the molecular basis of food ingredients, including genomic sequencing and pharmacological implications of food molecules, helps to reduce the impact of drug-food interactions. Various strategies are being leveraged to alleviate drug-food interactions; measures including patient engagement, digital health, approaches involving machine intelligence, and big data are a few of them. Furthermore, delineating the molecular communications across dietmicrobiome- drug-food-drug interactions in a pharmacomicrobiome framework may also play a vital role in personalized nutrition. Determining nutrient-gene interactions aids in making nutrition deeply personalized and helps mitigate unwanted drug-food interactions, chronic diseases, and adverse events from their onset. Translational bioinformatics approaches could play an essential role in the next generation of drug-food interaction research. In this landscape review, we discuss important tools, databases, and approaches along with key challenges and opportunities in drug-food interaction and its immediate impact on precision medicine.

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