Turner Richard M, Park B Kevin, Pirmohamed Munir
The Wolfson Centre for Personalised Medicine, Institute for Translational Medicine, University of Liverpool, Liverpool, UK.
MRC Centre for Drug Safety Science, Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK.
Wiley Interdiscip Rev Syst Biol Med. 2015 Jul-Aug;7(4):221-41. doi: 10.1002/wsbm.1302. Epub 2015 May 7.
There is notable interindividual heterogeneity in drug response, affecting both drug efficacy and toxicity, resulting in patient harm and the inefficient utilization of limited healthcare resources. Pharmacogenomics is at the forefront of research to understand interindividual drug response variability, but although many genotype-drug response associations have been identified, translation of pharmacogenomic associations into clinical practice has been hampered by inconsistent findings and inadequate predictive values. These limitations are in part due to the complex interplay between drug-specific, human body and environmental factors influencing drug response and therefore pharmacogenomics, whilst intrinsically necessary, is by itself unlikely to adequately parse drug variability. The emergent, interdisciplinary and rapidly developing field of systems pharmacology, which incorporates but goes beyond pharmacogenomics, holds significant potential to further parse interindividual drug variability. Systems pharmacology broadly encompasses two distinct research efforts, pharmacologically-orientated systems biology and pharmacometrics. Pharmacologically-orientated systems biology utilizes high throughput omics technologies, including next-generation sequencing, transcriptomics and proteomics, to identify factors associated with differential drug response within the different levels of biological organization in the hierarchical human body. Increasingly complex pharmacometric models are being developed that quantitatively integrate factors associated with drug response. Although distinct, these research areas complement one another and continual development can be facilitated by iterating between dynamic experimental and computational findings. Ultimately, quantitative data-derived models of sufficient detail will be required to help realize the goal of precision medicine.
药物反应存在显著的个体间异质性，这会影响药物疗效和毒性，导致患者受到伤害以及有限医疗资源的利用效率低下。药物基因组学处于理解个体间药物反应变异性研究的前沿，但尽管已经确定了许多基因 - 药物反应关联，药物基因组学关联在临床实践中的转化却受到结果不一致和预测价值不足的阻碍。这些局限性部分归因于影响药物反应的药物特异性、人体和环境因素之间的复杂相互作用，因此，药物基因组学虽然本身是必要的，但仅靠它不太可能充分解析药物变异性。新兴的、跨学科且快速发展的系统药理学领域，它整合了但又超越了药物基因组学，在进一步解析个体间药物变异性方面具有巨大潜力。系统药理学大致涵盖两项不同的研究工作，即以药理学为导向的系统生物学和药物计量学。以药理学为导向的系统生物学利用高通量组学技术，包括下一代测序、转录组学和蛋白质组学，来识别在人体层次结构中不同生物组织水平内与药物反应差异相关的因素。越来越复杂的药物计量模型正在被开发出来，这些模型定量整合与药物反应相关的因素。尽管这些研究领域各不相同，但它们相互补充，通过在动态实验结果和计算结果之间反复迭代可以促进持续发展。最终，将需要足够详细的定量数据驱动模型来帮助实现精准医学的目标。
