About this Research Topic
Network pharmacology is an emerging subject of systematic drug research in the era of artificial intelligence and big data. It is an original subject of fusion of pharmacology, system biology, bioinformatics, network science, and other related disciplines. Network pharmacology emphasizes the overall perspective of the system level and biological networks focusing on the analysis of the laws of molecular association between drugs and their treatment objects. It reveals the systematic pharmacological mechanisms of drugs and guides the research and development of new drugs into clinical diagnosis and treatment. With a network-based insight, network pharmacology intends to systematically reflect and reveal the biological foundation of complex diseases and drug effects. At the same time, a key concept that derived from the multi-targets nature of traditional medicine has been proposed, named “network target”, shifting away from the current “single target” research paradigm. The network target-based pharmacology is a promising strategy for the next generation of drug research and development for traditional medicine.
Recently, there has been a growing interest to use artificial intelligence and big omics data to study the “network target” underlying traditional medicine. Hopefully, with the current progress in network pharmacology research techniques, more network-based analytical approaches could be assimilated into such a medical field in order to accelerate the comprehension of traditional medicine and promote drug discovery. The potent network pharmacology may offer future therapeutic strategies that involve integrated treatments of complex disorders through targeting a specific network.
A particular challenge for network pharmacology in case of preparations derived from natural sources is the chemical diversity and complexity of extracts derived. This results in particular challenges for network pharmacology approaches since a complex system of compounds interacts with a complex set of targets (many to many relationships). This has often resulted in the identification of ubiquitous or trivial compounds as alleged ‘actives’. Numerous other problems will need to be overcome if extracts are to study successfully using network pharmacology. This specific Research Topic will focus on how such complex interactions can be understood better in scientific terms.
We welcome submissions on the development of novel treatments guided by network pharmacology, conducted in combination with experimental work or based on a sound body of experimental work. Subtopics may include:
- the understanding of the underlying mechanisms of action;
- the aid in the design of effective integrative clinical trials;
- the discovery of biologically active compounds, biomarkers for complex diseases, and optimizing traditional therapies.
Quality assurance
To conduct a high-quality selection of articles about network pharmacology and traditional medicine, all submitted articles will be evaluated based on the Network Pharmacology Evaluation Methodology Guidance, developed by the World Federation of Chinese Medicine Societies (WFCMS). The data collection, network analysis, and result validation will be assessed according to these standard guidelines, relying on three key aspects: reliability, standardization, and rationality.
Most importantly, potential authors will have to comply with the Journal guidelines for Network Pharmacology studies:
• In general, it is expected that network pharmacological studies will be conducted in combination with experimental work or are based on a sound body of experimental work.
• Network pharmacology studies must critically assess the evidence to evaluate the potential pharmacological effects of a preparation/herbal (medical) product and the limitations of the evidence.
• The network must be represented in such a way that the underlying mechanism can be understood including a suitable visualization of the network and the individual data points.
• The identification of the compounds must be sound. This information may be derived preferably from benchwork or else from the existing literature. It is essential that the quantities of the compounds in the preparation or plant are stated and are high enough to be of pharmacological relevance.
• The bioavailability of the compounds must be assessed.
• Ubiquitous or very widely known compounds are highly unlikely to be “active” especially in in vitro assays. Therefore, in these cases, evidence for therapeutic or preventive benefits and mechanisms of action is essential.
• The major target found by transcriptomics or proteomics needs to be validated by other experimental techniques.
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All the manuscripts submitted to this project will be peer-reviewed and need to fully comply with the Four Pillars of Best Practice in Ethnopharmacology (you can freely download the full version here).
Recently, there has been a growing interest to use artificial intelligence and big omics data to study the “network target” underlying traditional medicine. Hopefully, with the current progress in network pharmacology research techniques, more network-based analytical approaches could be assimilated into such a medical field in order to accelerate the comprehension of traditional medicine and promote drug discovery. The potent network pharmacology may offer future therapeutic strategies that involve integrated treatments of complex disorders through targeting a specific network.
A particular challenge for network pharmacology in case of preparations derived from natural sources is the chemical diversity and complexity of extracts derived. This results in particular challenges for network pharmacology approaches since a complex system of compounds interacts with a complex set of targets (many to many relationships). This has often resulted in the identification of ubiquitous or trivial compounds as alleged ‘actives’. Numerous other problems will need to be overcome if extracts are to study successfully using network pharmacology. This specific Research Topic will focus on how such complex interactions can be understood better in scientific terms.
We welcome submissions on the development of novel treatments guided by network pharmacology, conducted in combination with experimental work or based on a sound body of experimental work. Subtopics may include:
- the understanding of the underlying mechanisms of action;
- the aid in the design of effective integrative clinical trials;
- the discovery of biologically active compounds, biomarkers for complex diseases, and optimizing traditional therapies.
Quality assurance
To conduct a high-quality selection of articles about network pharmacology and traditional medicine, all submitted articles will be evaluated based on the Network Pharmacology Evaluation Methodology Guidance, developed by the World Federation of Chinese Medicine Societies (WFCMS). The data collection, network analysis, and result validation will be assessed according to these standard guidelines, relying on three key aspects: reliability, standardization, and rationality.
Most importantly, potential authors will have to comply with the Journal guidelines for Network Pharmacology studies:
• In general, it is expected that network pharmacological studies will be conducted in combination with experimental work or are based on a sound body of experimental work.
• Network pharmacology studies must critically assess the evidence to evaluate the potential pharmacological effects of a preparation/herbal (medical) product and the limitations of the evidence.
• The network must be represented in such a way that the underlying mechanism can be understood including a suitable visualization of the network and the individual data points.
• The identification of the compounds must be sound. This information may be derived preferably from benchwork or else from the existing literature. It is essential that the quantities of the compounds in the preparation or plant are stated and are high enough to be of pharmacological relevance.
• The bioavailability of the compounds must be assessed.
• Ubiquitous or very widely known compounds are highly unlikely to be “active” especially in in vitro assays. Therefore, in these cases, evidence for therapeutic or preventive benefits and mechanisms of action is essential.
• The major target found by transcriptomics or proteomics needs to be validated by other experimental techniques.
---
All the manuscripts submitted to this project will be peer-reviewed and need to fully comply with the Four Pillars of Best Practice in Ethnopharmacology (you can freely download the full version here).
Keywords: Network pharmacology, Traditional Medicine, Pharmacological effects, Experimental validation
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
