“Omics” in pharmaceutical research: overview, applications, challenges, and future perspectives

Yan, Shaomin; Liu, Runhui; Jin, Hui‐Zi; Liu, Xinru; Ye, Ji; Shan, Lei; Zhang, Wei‐Dong

doi:10.1016/s1875-5364(15)60002-4

Cited by 49 publications

(101 citation statements)

References 180 publications

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“…Many of these obstacles (both analytical and interpretative) are not unique to metabolomics, and also apply to emerging chemistry-based markers, proteomics, transcriptomics and genomics 19 , 79 , 101 . Therefore, both analytical technologies and computational methods are constantly advancing and evolving.…”

Section: Pragmatic Limitations In Applying Metabolomics To Large Intementioning

confidence: 99%

Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future: Table 1.

et al. 2016

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Metabolomics and lipidomics are emerging methods for detailed phenotyping of small molecules in samples. It is hoped that such data will: (i) enhance baseline prediction of patient response to pharmacotherapies (beneficial or adverse); (ii) reveal changes in metabolites shortly after initiation of therapy that may predict patient response, including adverse effects, before routine biomarkers are altered; and( iii) give new insights into mechanisms of drug action, particularly where the results of a trial of a new agent were unexpected, and thus help future drug development. In these ways, metabolomics could enhance research findings from intervention studies. This narrative review provides an overview of metabolomics and lipidomics in early clinical intervention studies for investigation of mechanisms of drug action and prediction of drug response (both desired and undesired). We highlight early examples from drug intervention studies associated with cardiometabolic disease. Despite the strengths of such studies, particularly the use of state-of-the-art technologies and advanced statistical methods, currently published studies in the metabolomics arena are largely underpowered and should be considered as hypothesis-generating. In order for metabolomics to meaningfully improve stratified medicine approaches to patient treatment, there is a need for higher quality studies, with better exploitation of biobanks from randomized clinical trials i.e. with large sample size, adjudicated outcomes, standardized procedures, validation cohorts, comparison witth routine biochemistry and both active and control/placebo arms. On the basis of this review, and based on our research experience using clinically established biomarkers, we propose steps to more speedily advance this area of research towards potential clinical impact.

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Section: Pragmatic Limitations In Applying Metabolomics To Large Intementioning

confidence: 99%

Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future: Table 1.

et al. 2016

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“…The development and validation of sensitive, accurate, and precise analytical methods are the critical step in new drug discovery and development [4, 24–27] , especially for natural products [4, 24–26] . Several of our marine analogs have entered the preclinical development for the treatment of human cancers [6–14, 19–20] ; the UPLC-MS/MS method developed for analysis of TCBA-TPQ and initial pharmacokinetic study would have a significant impact on future research and development of this agent and related analogs as well.…”

Section: Resultsmentioning

confidence: 99%

Development and validation of an HPLC-MS/MS analytical method for quantitative analysis of TCBA-TPQ, a novel anticancer makaluvamine analog, and application in a pharmacokinetic study in rats

Jin

Voruganti

et al. 2015

Chinese Journal of Natural Medicines

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We have recently designed and synthesized several novel iminoquinone anticancer agents that have entered preclinical development for the treatment of human cancers. Herein we developed and validated a quantitative HPLC-MS/MS analytical method for one of the lead novel anticancer makaluvamine analog, TCBA-TPQ, and conducted a pharmacokinetic study in laboratory rats. Our results indicated that the HPLC-MS/MS method was precise, accurate, and specific. Using this method, we carried out in vitro and in vivo evaluations of the pharmacological properties of TCBA-TPQ and plasma pharmacokinetics in rats. Our results provide a basis for future preclinical and clinical development of this promising anticancer marine analog.

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“…Additionally, biological molecules such as genes, proteins, and metabolites are dynamic. Even for the same individual under the same analytical conditions, the data will be analyzed as static and may not be representative of the dynamic nature of biological processes . Thus, unbiased interpretation of the data can be problematic.…”

Section: Limitations Of Current Omics Technologiesmentioning

confidence: 99%

“…Interpretation of the data from one omics approach is already challenging. Thus, combining data from multiple types of applications renders interpretation exceedingly challenging and prone to bias . A potential solution is to build network maps for biological processes based on the data obtained from multiple omics studies, which rely on the accuracy of the data science management .…”

Section: Limitations Of Current Omics Technologiesmentioning

confidence: 99%

The Age of Omics‐Driven Precision Medicine

McColl

Asthana

Paine

et al. 2019

Clin Pharma and Therapeutics

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“Omics” in pharmaceutical research: overview, applications, challenges, and future perspectives

Cited by 49 publications

References 180 publications

Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future: Table 1.

Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future: Table 1.

Development and validation of an HPLC-MS/MS analytical method for quantitative analysis of TCBA-TPQ, a novel anticancer makaluvamine analog, and application in a pharmacokinetic study in rats

The Age of Omics‐Driven Precision Medicine

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