Institute of Phytopharmacological Research
Advancing the science of medicinal plants through AI-driven research and structured knowledge systems
New publication: "Structured Ontologies and Databases for AI-Driven Phytopharmacology" -Read more
Our Research Focus
Bridging traditional herbal knowledge with modern science through innovative ontologies and AI-powered databases
Our team creates comprehensive ontologies that link traditional herbal knowledge with modern biomedical concepts, enabling seamless integration with clinical data.
We compile and structure data on medicinal herbs, their chemical constituents, therapeutic uses, and clinical evidence to support evidence-based phytotherapy.
Our AI systems analyze complex relationships between herbs, compounds, diseases, and genes to discover new therapeutic applications and improve clinical decision support.
Featured Research
Structured Ontologies for Phytopharmacology
Our latest research focuses on developing comprehensive ontologies that bridge traditional herbal knowledge with modern biomedical concepts. By leveraging standard biomedical ontologies like MeSH, UMLS, and ChEBI, we create a rich semantic network linking medicinal plants to their constituents, indications, and related concepts.
This work enables the integration of herbal medicine data with conventional medical systems, supporting evidence-based phytotherapy and facilitating drug discovery from natural sources.
Key Applications
Evidence-Based Phytotherapy
Supporting clinicians with structured evidence on herbal treatments
Drug Discovery
Accelerating the identification of novel therapeutic compounds from plants
Clinical Decision Support
Integrating herbal medicine data into healthcare systems
Personalized Medicine
Tailoring herbal treatments based on individual patient profiles
Latest Publications
This paper explores how standard biomedical ontologies beyond SNOMED CT can be leveraged to build comprehensive phytopharmacology knowledge bases.
A comprehensive review of 25 medicinal herb databases, examining their content, functionality, and potential for integration with AI systems.
This study demonstrates how semantic web technology and AI can be applied to herbal medicine data, creating powerful knowledge graphs for research and clinical applications.
Join Our Research Network
Collaborate with us to advance the science of phytopharmacology and develop innovative solutions for healthcare