Herbal medicines are widely used worldwide, independently or combined
with conventional drugs, due to their natural origin and perceived safety. However,
there is a major concern about the possibility of Herb-Drug Interactions (HDIs),
especially given the complex biochemical compositions of herbal products. As more
people take herbal supplements in addition to prescription drugs, herb-drug
interactions, or HDIs, are becoming more common. Several active chemicals found in
herbs can influence the way medications are absorbed, metabolised, or eliminated,
potentially resulting in adverse side effects or decreased medication effectiveness.
Predicting these interactions is challenging due to the absence of regulation and
standardisation of herbal products and the lack of research on HDIs, necessitating more
targeted research. Bioinformatics has emerged as a powerful tool to understand,
predict, and mitigate HDIs by using computational approaches. By using computational
methods to analyse extensive biological datasets for the purpose of researching and
forecasting Herb-Drug Interactions (HDIs), bioinformatics plays a crucial role in
furthering this field of inquiry. Furthermore, the establishment of databases specifically
tailored to the Human Development Index (HDI) and the formulation of predictive
models are examined, offering significant resources for academic researchers and
healthcare practitioners. This article reviews recent advances in bioinformatics
applications to HDIs, including databases and algorithms that provide insights into how
computational methods can advance our understanding of HDIs and improve patient
safety.
Keywords: Bioinformatics, Clinical Decision Support Systems (CDSS), Clinical implications, Computational modelling, Cytochrome P interactions, Drug resistance and drug discovery, Herb-Drug interactions, Metabolite profiling, Molecular docking, Traditional Chinese Medicine- Integrated Database (TCMID).
