Approaches in studying the pharmacology of Chinese Medicine formulas: Bottom-up, top-down-and meeting in the middle

Tao Huang, Lidan Zhong, Chen Yuan Lin, Ling Zhao, Zi Wan Ning, Dong Dong Hu, Man Zhang, Ke Tian, Chung Wah Cheng, Zhaoxiang Bian*, MZRW Research Group

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

13 Citations (Scopus)


Investigating the pharmacology is key to the modernization of Chinese Medicine (CM) formulas. However, identifying which are the active compound(s) of CM formulas, which biological entities they target, and through which signaling pathway(s) they act to modify disease symptoms, are still difficult tasks for researchers, even when equipped with an arsenal of advanced modern technologies. Multiple approaches, including network pharmacology, pharmaco-genomics, -proteomics, and -metabolomics, have been developed to study the pharmacology of CM formulas. They fall into two general categories in terms of how they tackle a problem: bottom-up and top-down. In this article, we compared these two different approaches in several dimensions by using the case of MaZiRenWan (MZRW, also known as Hemp Seed Pill), a CM herbal formula for functional constipation. Multiple hypotheses are easy to be proposed in the bottom-up approach (e.g. network pharmacology); but these hypotheses are usually false positives and hard to be tested. In contrast, it is hard to suggest hypotheses in the top-down approach (e.g. pharmacometabolomics); however, once a hypothesis is proposed, it is much easier to be tested. Merging of these two approaches could results in a powerful approach, which could be the new paradigm for the pharmacological study of CM formulas.

Original languageEnglish
Article number15
JournalChinese Medicine
Issue number1
Publication statusPublished - 21 Mar 2018

Scopus Subject Areas

  • Pharmacology
  • Complementary and alternative medicine

User-Defined Keywords

  • Bottom-up
  • Chinese medicine formula
  • Focused network pharmacology
  • Pharmacometabolomics
  • Top-down


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