Longitudinal pharmacometabonomics for predicting patient responses to therapy: drug metabolism, toxicity and efficacy

Pharmacometabonomics describes the use of metabolic profiling of biofluids, tissues and tissue extracts to predict, prior to dosing, the beneficial and adverse effects of an intervention such as drug administration. The approach not only is analogous to pharmacogenomics but also is sensitive to environmental factors such as the gut microbiome. Recent applications of pharmacometabonomics are presented and the extension to the use of longitudinal sampling is introduced. Clinical and other human applications of pharmacometabonomics are highlighted and possible future clinical applications of pharmacometabonomics and longitudinal pharmacometabonomics are discussed. These include clinical trials of new drugs either at the first-into-man stage or later in Phase II and III trials, and assessment of individual patients or groups of patients for particular therapies (personalised and stratified medicine approaches). Since metabonomics approaches are sensitive to both the host genome effects and the gut microbiome, pharmacometabonomics has particular utility for studying the host-microbiome interactions and for assessing new therapies that target the gut bacteria. Since the microbiome also has implications for nutrition and drug pharmacokinetics, such metabolic profiling approaches are likely to of use in such studies. It is anticipated that as metabonomics analytical and statistical technologies continue to develop, more applications will be realised and these should find use in real clinical situations, even monitoring patients in real time.     

代谢组学分析技术及代谢物鉴定

近年来,代谢组学技术在众多科学领域得到了广泛的应用。代谢组学研究的关键在于对大量小分子代谢产物进行快速、准确的分析鉴定,这在很大程度上依赖于相关技术的进步。磁共振、质谱、色谱以及毛细管电泳等技术的发展和联用,使得代谢组学的广泛应用成为可能。磁共振和质谱是代谢组学研究中最重要的两个技术平台,对代谢产物进行明确的鉴定是代谢组学研究的根本任务。本文就代谢组学相关分析技术及代谢物鉴定的研究进展作一综述。     

代谢组学的发展与药物研究开发

代谢组学是近年来新发展起来的一门组学,其主要研究体系有生物体液、生物组织及单个细胞的代谢组,利用一些现代的分析技术,如NMR、LC-MS、GC-MS等,取得整个研究体系的多维数据后,利用模式识别和专家系统技术寻找其中的系统生物学信息。本文从代谢组学的发展,代谢组学的研究范围和研究方法,以及在药物的作用机制和安全性评价,疾病模型,特别是中药研究的应用等方面予以阐述。     

Systems-ADME/Tox: resources and network approaches

The increasing cost of drug development is partially due to our failure to identify undesirable compounds at an early enough stage of development. The application of higher throughput screening methods have resulted in the generation of very large datasets from cells in vitro or from in vivo experiments following the treatment with drugs or known toxins. In recent years the development of systems biology, databases and pathway software has enabled the analysis of the high-throughput data in the context of the whole cell. One of the latest technology paradigms to be applied alongside the existing in vitro and computational models for absorption, distribution, metabolism, excretion and toxicology (ADME/Tox) involves the integration of complex multidimensional datasets, termed toxicogenomics. The goal is to provide a more complete understanding of the effects a molecule might have on the entire biological system. However, due to the sheer complexity of this data it may be necessary to apply one or more different types of computational approaches that have as yet not been fully utilized in this field. The present review describes the data generated currently and introduces computational approaches as a component of ADME/Tox. These methods include network algorithms and manually curated databases of interactions that have been separately classified under systems biology methods. The integration of these disparate tools will result in systems-ADME/Tox and it is important to understand exactly what data resources and technologies are available and applicable. Examples of networks derived with important drug transporters and drug metabolizing enzymes are provided to demonstrate the network technologies.     

Integration of genomic and metabonomic data in systems biology--are we 'there' yet?

The measurement of genes, proteins and metabolites has gained increasing acceptance as a means by which to study the response of an organism to stimuli, whether they are environmental, genetic, pharmacological, toxicological, etc. Typically referred to as genomics, proteomics, and metabonomics or metabolomics, respectively, these methods as independent entities have undoubtedly provided new biological insight that was not attainable a decade ago. Not surprisingly, scientists continue to push the boundaries to extract knowledge from data, and it is currently recognized that the full realization of these technologies is limited by a lack of tools to enable data integration. Integration of these 'omic datasets, or integromics, is desirable as it links the individual biological elements together to provide a more complete understanding of dynamic biological processes. Accordingly, in addition to developing new data analysis methods to extract further details from each of the high-content datasets individually, effort is also being expended to create or improve statistical methods, databases, annotations and pathway mapping to maximize our learning. There are several recent examples, in both mammalian and non-mammalian systems, in which genes, proteins and/or metabolites have been integrated using either biology- or data-driven strategies. Herein, key findings are reviewed, gaps in our current tools and technologies are identified and illustrated, and perspective is provided on the potential of integromics in biological research.     

Ecotoxicogenomics: linkages between exposure and effects in assessing risks of aquatic contaminants to fish

Understanding the biological effects of exposures to chemicals in the environment relies on classical methods and emerging technologies in the areas of genomics, proteomics, and metabonomics. Linkages between the historical and newer toxicological tools are currently being developed in order to predict and assess risk. Being able to classify chemicals and other stressors based on effects they have at the molecular, tissue, and organismal levels helps define a systems biology approach to development of streamlined, cost-effective, and comprehensive testing approaches for evaluating environmental hazards. The challenges of the individual technologies and the combinations of tools for ecotoxicogenomics are discussed in application to aquatic toxicology with a particular emphasis on fish testing.     

Overview of the metallometabolomic methodology for metal-based drug metabolism

Metallometabolomics is an emerging field integrating the research technologies related to the comprehensive analysis of metabolites of a metallodrug in a biologically relevant sample, requiring high-throughput and targeted analyses of the transformation, speciation, localization and structural characteristics of the metallometabolites. This review discusses the concept of metallometabolomics with a focus on analytical techniques and methods, particularly the hyphenated approaches that combine high resolution separation techniques (liquid chromatography or capillary electrophoresis) with highly sensitive detection methods such as mass spectrometry (elemental (ICP) or molecular (ESI)) or nuclear analytical methods (X-ray fluorescence/absorption/emission/diffraction and nuclear magnetic resonance). The application of these advanced analytical technologies in the speciation analysis, identity determination and structural elucidation of metallometabolites will be selectively outlined, along with their advantages and limitations.     

Application of metabonomic analytical techniques in the modernization and toxicology research of traditional Chinese medicine

In the recent years, a wide range of metabonomic analytical techniques are widely used in the modern research of traditional Chinese medicine (TCM). At the same time, the international community has attached increasing importance to TCM toxicity problems. Thus, many studies have been implemented to investigate the toxicity mechanisms of TCM. Among these studies, many metabonomic-based methods have been implemented to facilitate TCM toxicity investigation. At present, the most prevailing methods for TCM toxicity research are mainly single analysis techniques using only one analytical means. These techniques include nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-mass spectrometry (LC-MS), etc.; with these techniques, some favourable outcomes have been gained in the toxic reaction studies of TCM, such as the action target organs assay, the establishment of action pattern, the elucidation of action mechanism and the exploration of action material foundation. However, every analytical technique has its advantages and drawbacks, no existing analytical technique can be versatile. Multi-analysed techniques can partially overcome the shortcomings of single-analysed techniques. Combination of GC-MS and LC-MS metabolic profiling approaches has unravelled the pathological outcomes of aristolochic acid-induced nephrotoxicity, which can not be achieved by single-analysed techniques. It is believed that with the further development of metabonomic analytical techniques, especially multi-analysed techniques, metabonomics will greatly promote TCM toxicity research and be beneficial to the modernization of TCM in terms of extending the application of modern means in the TCM safety assessment, assisting the formulation of TCM safety norms and establishing the international standards indicators.     

Metabonomics Techniques and Applications to Pharmaceutical Research & Development

In this review, the background to the approach known as metabonomics is provided, giving a brief historical perspective and summarizing the analytical and statistical techniques used. Some of the major applications of metabonomics relevant to pharmaceutical Research & Development are then reviewed including the study of various influences on metabolism, such as diet, lifestyle, and other environmental factors. The applications of metabonomics in drug safety studies are explained with special reference to the aims and achievements of the Consortium for Metabonomic Toxicology. Next, the role that metabonomics might have in disease diagnosis and therapy monitoring is provided with some examples, and the concept of pharmacometabonomics as a way of predicting an individual's response to treatment is highlighted. Some discussion is given on the strengths and weaknesses, opportunities of, and threats to metabonomics.     

整合代谢组学和生物信息学策略在解析中药系统复杂性中的应用

中药在化学组成方面的复杂性决定了其作用方式和作用过程的复杂性。传统研究方法缺乏系统性,使得一系列制约中药现代化发展的关键问题一直未能得到很好的解决,包括中药化学物质组表征、中药作用机制、中药方剂配伍规律以及中药毒性机制等中药系统复杂性问题。代谢组学作为一门全新的组学技术,秉承了从机体全局系统出发来考量机体内源性小分子物质与外源性干预物质（如药物）的相互作用的理念,与在中医药理论指导下的中药作用原理思路一致。近年来,人们尝试将整合代谢组学技术和生物信息学策略用于解开上述中药关键问题,并已取得了一定的成果。但其在理论挖掘、策略设计、方法开发和实践拓展诸多方面都有很多具体的工作需要进一步推进。对整合代谢组学和生物信息学策略在解析中药系统复杂性中的应用进行综述。     

代谢组学在肝肾损伤研究中的应用

代谢组学是近年来新发展起来的一门组学,已成为生物医学研究领域的新热点.由于其广泛的应用前景,目前已是系统生物学的重要组成部分.肝损伤及肾损伤是临床常见的危害人类健康的疾病,但目前的指标缺乏特异性,且灵敏度不高,造成临床上难以对肝肾损伤做出准确而及时的预警和监测.代谢组学能从代谢的角度整体分析疾病,快速、安全地对疾病的严重程度进行判别,在肝肾损伤的早期诊断等方面的研究已初显优势.本文主要综述了代谢组学技术在肝肾损伤研究中的应用现状.     

Genomics, proteomics and metabonomics in toxicology: hopefully not 'fashionomics'

Genomics, proteomics and metabonomics are applied to toxicology either as stand-alone technologies or in combination, with the intention of providing a more efficient assessment of the potential side effects of new chemical entities. Two different approaches are taken: a predictive/proactive strategy based on a statistical analogy of 'signatures' of drugs to many known toxicant gene or metabolite fingerprints; and a mechanistic/reactive strategy based on the in-depth biological analysis of the gene, protein or metabolite profiles induced by one or a few compounds of interest. This article focuses on the advantages and disadvantages of these technologies, as well as the many hurdles associated with both these approaches in toxicology that have to be considered before applying them to the assessment of future drugs.     

细胞代谢组学及其应用

细胞代谢组学通常被定义为胞内和细胞膜小分子代谢物的集合,而代谢物参与胞内进程的多种变化,其浓度可近似地反映一个器官、组织或细胞的表型。细胞代谢组学是一个新兴发展的领域,它可解决基本的生物学问题,并允许观察细胞内的代谢现象。在后基因时代,与当前其他常用的方法相比,细胞代谢组学具有许多潜在的优势,已成为一个有前途的分析工具。现简要综述细胞代谢组学的主要研究流程及其应用、与其他组学联用等方面的研究进展。     

Protein instability and immunogenicity: roadblocks to clinical application of injectable protein delivery systems for sustained release

Protein instability and immunogenicity are two main roadblocks to the clinical success of novel protein drug delivery systems. In this commentary, we discuss the need for more extensive analytical characterization in relation to concerns about protein instability in injectable drug delivery systems for sustained release. We then will briefly address immunogenicity concerns and outline current best practices for using state-of-the-art analytical assays to monitor protein stability for both conventional and novel therapeutic protein dosage forms. Next, we provide a summary of the stresses on proteins arising during preparation of drug delivery systems and subsequent in vivo release. We note the challenges and difficulties in achieving the absolute requirement of quantitatively assessing the degradation of protein molecules in a drug delivery system. We describe the potential roles for academic research in further improving protein stability and developing new analytical technologies to detect protein degradation byproducts in novel drug delivery systems. Finally, we provide recommendations for the appropriate approaches to formulation design and assay development to ensure that stable, minimally immunogenic formulations of therapeutic proteins are created. These approaches should help to increase the probability that novel drug delivery systems for sustained protein release will become more readily available as effective therapeutic agents to treat and benefit patients.     

代谢物组学的研究进展

代谢物组学是继基因组学和蛋白质组学发展起来的一门新的组学(-omics)技术,是研究药物毒理和基因功能的技术平台,通过分析生物的体液、组织中的内源性代谢产物谱的变化来研究整体的生物学状况和基因调节功能.代谢物组学所涉及的主要技术为核磁共振技术和模式识别分析.对代谢物组学研究的样品、核心技术、分析方法和应用等几方面作简要概述.     

Computational strategies for metabolite identification in metabolomics

Most metabolomic data are characterized by complex spectra or chromatograms containing hundreds of peaks or features. While there are many methods for aligning or comparing these spectral features, there are few approaches for actually identifying which peaks match to which compounds. Indeed, one of the biggest unmet needs in the field of metabolomics lies in the problem of compound identification. This review describes some of the newly emerging computational strategies in metabolomics that are being used to aid in the identification of metabolites from biofluid mixtures analyzed by NMR and MS. The most successful compound-identification strategies typically involve matching spectral features of the unknown compound(s) to curated spectral databases of reference compounds. This approach is known as the identification of 'known unknowns'. However, the identification of truly novel compounds (the 'unknown unknowns') is particularly challenging and requires the use of computer-aided structure elucidation methods being applied to the purified compound. The strengths and limitations of these approaches as applied to different analytical technologies (GC-MS, LC-MS and NMR) will be discussed, as will prospects for potential improvements to existing strategies.     

Intracochlear drug delivery systems

INTRODUCTION: Advances in molecular biology and in the basic understanding of the mechanisms associated with sensorineural hearing loss and other diseases of the inner ear are paving the way towards new approaches for treatments for millions of patients. However, the cochlea is a particularly challenging target for drug therapy, and new technologies will be required to provide safe and efficacious delivery of these compounds. Emerging delivery systems based on microfluidic technologies are showing promise as a means for direct intracochlear delivery. Ultimately, these systems may serve as a means for extended delivery of regenerative compounds to restore hearing in patients suffering from a host of auditory diseases. AREAS COVERED: Recent progress in the development of drug delivery systems capable of direct intracochlear delivery is reviewed, including passive systems such as osmotic pumps, active microfluidic devices and systems combined with currently available devices such as cochlear implants. The aim of this article is to provide a concise review of intracochlear drug delivery systems currently under development and ultimately capable of being combined with emerging therapeutic compounds for the treatment of inner ear diseases. EXPERT OPINION: Safe and efficacious treatment of auditory diseases will require the development of microscale delivery devices, capable of extended operation and direct application to the inner ear. These advances will require miniaturization and integration of multiple functions, including drug storage, delivery, power management and sensing, ultimately enabling closed-loop control and timed-sequence delivery devices for treatment of these diseases.     

Application of combinatorial chemistry to antimicrobial drug discovery

The emergence of pathogens resistant to currently available treatments is seen as a public health crisis. Since few new classes of antimicrobial drugs have been developed in the last two decades, it is becoming increasingly probable that healthcare providers will be faced with infections for which no chemotherapeutic agent is available. A renewed emphasis is being placed on employing the most advanced drug discovery technologies in the development of new antimicrobials. The recently introduced technologies of combinatorial chemistry offer new sources of chemical diversity, as well as methods with which to produce and rapidly test them. In the last few years, many groups have adopted a number of approaches in order to apply combinatorial chemistry to antimicrobial drug discovery. These combinatorial strategies, and the manner in which they are used to develop new screening formats or to identify new chemical leads are, reviewed.