Abstract
Depression is a highly prevalent disorder that affects more than 300 million adults worldwide in 2015. Depression also frequently coexists with many other conditions such as osteoporosis and one-third of the Intensive Care Unit (ICU) survivors had depressive symptoms. Antidepressants have become the most commonly prescribed drugs in the United States. In addition to the regular process, drug discovery and development (R&D) for depression presents extra challenges because of the heterogeneity of the symptoms and various co-occurring disorders. Botanical medicine with multi-functional nature has been proposed to be more effective, providing rapid control of core and comorbid conditions of depression. With the technical advances in analytical instruments, metabolomics is entering into a “new generation”. Next-generation metabolomics (NGM) has the capability to comprehensively characterize drug-induced metabolic changes in the biological systems. NGM has demonstrated great potential in all the stages of pharmaceutical R&D in the last 10 years. Albiflorin isolated from Peony roots is a promising drug candidate with multi-target for depression and is currently under development by Beijing Wonner Biotech. In this work, we summarized the common analytical platforms for NGM and its main applications in drug R&D. We used albiflorin as an example to illustrate how NGM improves our understanding of drug candidate actions and facilitates drug safety evaluation. Future directions on how to expand the use of NGM for new antidepressant development in pharmaceutical industry were also discussed.
Keywords: Metabolomics, antidepressants, drug development and discovery, albiflorin, depression, next-generation metabolomics (NGM).
Current Pharmaceutical Design
Title:Next-generation Metabolomics in the Development of New Antidepressants: Using Albiflorin as an Example
Volume: 24 Issue: 22
Author(s): Jian Han, Yonghong Xia, Lejun Lin, Zuoguang Zhang, Hui Tian and Kefeng Li*
Affiliation:
- School of Medicine, University of California, San Diego, CA, 92103,United States
Keywords: Metabolomics, antidepressants, drug development and discovery, albiflorin, depression, next-generation metabolomics (NGM).
Abstract: Depression is a highly prevalent disorder that affects more than 300 million adults worldwide in 2015. Depression also frequently coexists with many other conditions such as osteoporosis and one-third of the Intensive Care Unit (ICU) survivors had depressive symptoms. Antidepressants have become the most commonly prescribed drugs in the United States. In addition to the regular process, drug discovery and development (R&D) for depression presents extra challenges because of the heterogeneity of the symptoms and various co-occurring disorders. Botanical medicine with multi-functional nature has been proposed to be more effective, providing rapid control of core and comorbid conditions of depression. With the technical advances in analytical instruments, metabolomics is entering into a “new generation”. Next-generation metabolomics (NGM) has the capability to comprehensively characterize drug-induced metabolic changes in the biological systems. NGM has demonstrated great potential in all the stages of pharmaceutical R&D in the last 10 years. Albiflorin isolated from Peony roots is a promising drug candidate with multi-target for depression and is currently under development by Beijing Wonner Biotech. In this work, we summarized the common analytical platforms for NGM and its main applications in drug R&D. We used albiflorin as an example to illustrate how NGM improves our understanding of drug candidate actions and facilitates drug safety evaluation. Future directions on how to expand the use of NGM for new antidepressant development in pharmaceutical industry were also discussed.
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Cite this article as:
Han Jian , Xia Yonghong, Lin Lejun, Zhang Zuoguang , Tian Hui and Li Kefeng*, Next-generation Metabolomics in the Development of New Antidepressants: Using Albiflorin as an Example, Current Pharmaceutical Design 2018; 24 (22) . https://dx.doi.org/10.2174/1381612824666180727114134
DOI https://dx.doi.org/10.2174/1381612824666180727114134 |
Print ISSN 1381-6128 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4286 |
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