College of Pharmaceutical Sciences in Zhejiang University, China.
Department of Bioinformatics in Chongqing Medical University, China.
Brief Bioinform. 2021 Sep 2;22(5). doi: 10.1093/bib/bbab138.
Individual variations in drug efficacy, side effects and adverse drug reactions are still challenging that cannot be ignored in drug research and development. The aim of pharmacometabonomics is to better understand the pharmacokinetic properties of drugs and monitor the drug effects on specific metabolic pathways. Here, we systematically reviewed the recent technological advances in pharmacometabonomics for better understanding the pathophysiological mechanisms of diseases as well as the metabolic effects of drugs on bodies. First, the advantages and disadvantages of all mainstream analytical techniques were compared. Second, many data processing strategies including filtering, missing value imputation, quality control-based correction, transformation, normalization together with the methods implemented in each step were discussed. Third, various feature selection and feature extraction algorithms commonly applied in pharmacometabonomics were described. Finally, the databases that facilitate current pharmacometabonomics were collected and discussed. All in all, this review provided guidance for researchers engaged in pharmacometabonomics and metabolomics, and it would promote the wide application of metabolomics in drug research and personalized medicine.
药物疗效、副作用和不良反应的个体差异仍然是药物研发中不可忽视的挑战。药物代谢组学的目的是更好地了解药物的药代动力学特性，并监测药物对特定代谢途径的影响。在这里，我们系统地回顾了药物代谢组学的最新技术进展，以更好地了解疾病的病理生理机制以及药物对身体的代谢影响。首先，比较了所有主流分析技术的优缺点。其次，讨论了许多数据处理策略，包括过滤、缺失值插补、基于质量控制的校正、转换、归一化以及每个步骤中实施的方法。第三，描述了药物代谢组学中常用的各种特征选择和特征提取算法。最后，收集并讨论了有助于当前药物代谢组学的数据库。总之，本综述为从事药物代谢组学和代谢组学的研究人员提供了指导，并将促进代谢组学在药物研究和个性化医学中的广泛应用。
