Systems Network Pharmaco-Toxicology in the Study of Herbal Medicines

  • Alessandro BurianiEmail author
  • Stefano Fortinguerra
  • Maria Carrara
  • Olavi Pelkonen


Analytic “‘omic” techniques and systems biology driven bioinformatics have increasingly been a game changer in the study of herbal drugs, thanks to the simultaneous detection of entire molecular families in a given biological system, and the ability to collect, classify, network, and visualize a large number of analytical data through bioinformatics. The genomics area has been at the vanguard of this evolution. Other “‘omic” techniques, such as proteomics and metabonomics, are providing a fast-growing body of data both on biological targets and on phytocomplexes and their interactions. This has favored a more global view of biological processes, describing how perturbations can influence the steady state of a large number of the components of the system and their relations, changing the system as a whole. It is thus apparent that biological responses induced by phytocomplexes represent the net output of changes in the properties of a very large number of molecules, all acting in an interdependent fashion to form a highly connected network.

“‘Omic” techniques and systems biology are applied in herbal medicine at various levels, and provide novel strategies that can be exploited both for herbal drug research and medical use, in applications ranging from drug quality control to patient stratification. Network pharmaco-toxicology represents one of the most important applications of this new approach. Building up networks of molecular interactions between phytocomplex components and pharmaco-toxicological processes can provide a powerful predictive tool in herbal medicine. There is an increasing number of Web-based systems biology platforms, continuously fed with “'omics” data, providing a view of the complete biological system modulated by a given drug that can be used for predictive pharmacology and toxicology. Systems toxicology promises to be the best context for providing a mechanistic understanding of toxicological effects, thus allowing the prediction of responses to phytochemicals.


‘omics Pharmacogenomics Genomics Whole genome sequencing Natural drugs Proteomics Metabonomics Metabolomics Microbiome Systems biology Network pharmacology Network toxicology Herbal medicines Phytocomplex Holistic Traditional Chinese medicine Ayurveda Jamu Kampo Traditional Iranian medicine 



Adsorption, distribution, metabolism, excretion


Adsorption, distribution, metabolism, excretion and toxicology


Adverse outcome pathway


Addition and subtraction theory


Connectivity map


Da Chaihu decoction


Drug-induced liver injury


Food and Drug Administration


Human metabolome database


Herbal medicine systems pharmacology


UK National Health System


Kyoto Encyclopedia of Genes and Genomes


Ligand-based virtual screening


Library of integrated network-based cellular signatures


Ma-huang decoction


Mass spectrometry


Next generation sequencing


(United States) National Institutes of Health


Nuclear magnetic resonance


Probability ensemble approach


Personal genome project


Pathways of toxicity


Parallel reaction monitoring


Quantitative structure-activity relationships


Structure-based virtual screening


Single nucleotide polymorphisms


Selected reaction monitoring


Traditional Chinese medicine


Traditional Chinese medicine systems pharmacology database


Virtual screening


Whole exome sequencing


Xiao Chaihu decoction


Whole genome sequencing



We would like to thank Roberta Sato at the Library of the Department of Pharmaceutical and Pharmacological Sciences of the University of Padova for her technical assistance with database search and bibliography, and Mariagnese Barbera for text revision.

Conflict of Interest

Alessandro Buriani and Stefano Fortinguerra are in charge of the Personalized Medicine service of the Gruppo Data Medica Padova.


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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Alessandro Buriani
    • 1
    • 2
    Email author
  • Stefano Fortinguerra
    • 1
    • 2
  • Maria Carrara
    • 2
  • Olavi Pelkonen
    • 3
  1. 1.Center Maria Paola Belloni Regazzo for Pharmacogenomics and Personalized MedicineGruppo Data MedicaPadovaItaly
  2. 2.Department of Pharmacological and Pharmaceutical SciencesUniversity of PadovaPadovaItaly
  3. 3.Department of Pharmacology and ToxicologyUniversity of OuluOuluFinland

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