Related Experiment Video
Updated: Jun 25, 2026
08:44
Elucidation of the Material Basis of Yiqi Qingjie Formula Against IgA Nephropathy Using UHPLC-Q-Orbitrap HRMS Integrated with Network Pharmacology
Published on: May 19, 2026
Metapath-guided transfer learning with clinical validation for identifying herb-drug interactions
Won-Yung Lee1, Kyoung Hoon Mo2, Surin Kim3
1School of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea.
Summary
A new deep learning framework, Meta-HDI, accurately predicts herb-drug interactions (HDIs) and confirms clinical effects. This tool aids in understanding complex interactions for safer co-administration of drugs and herbal products.
Area of Science:
- Computational pharmacology and bioinformatics
- Pharmacokinetics and drug metabolism
- Systems biology and network pharmacology
Background:
- Drug co-administration can lead to significant pharmacokinetic interactions, altering drug metabolism and efficacy.
- Herb-drug interactions (HDIs) are challenging to predict due to limited validated cases and the chemical complexity of herbal products.
Purpose of the Study:
- To develop Meta-HDI, a novel metapath-guided transfer-learning framework for enhanced prediction and interpretability of HDIs.
- To leverage large drug-drug interaction graphs to improve prediction accuracy for herb-drug interactions.
- To prospectively validate Meta-HDI predictions at the clinical pharmacokinetic level.
Main Methods:
- Integration of a deep learning framework (GCN encoder, shortest-path LSTM, hierarchical attention) with a prospective clinical crossover trial and in vitro assays.
- Benchmarking Meta-HDI against existing models across various in vivo HDI classes and clinical scenarios.
- Prospective evaluation of predicted interactions between donepezil and specific herbal formulas, followed by mechanistic validation using human liver microsome assays.
Main Results:
- Meta-HDI significantly improved prediction performance (micro-averaged AUROC 0.95) and correctly classified all evaluated clinical cases.
- Clinical trial demonstrated that co-administration of herbal formulas increased donepezil exposure without adverse events.
- Mechanistic validation identified specific compounds (falcarinol, glabranin) as CYP2D6 inhibitors, explaining the observed interaction.
Conclusions:
- Meta-HDI effectively addresses the scarcity of HDI data, offering mechanistic and clinically interpretable predictions.
- The framework shows promise for clinical decision support in managing herb-drug co-administration.
- Further validation across a wider range of drugs and herbal products is recommended to broaden applicability.
Related Concept Videos
01:30Drug toxicity: Drug–Drug Interaction
Drug–drug interactions can precipitate toxicity through multiple mechanisms. Absorption interactions alter how drugs enter the body, exemplified when ranitidine increases the absorption of basic drugs, while cholestyramine decreases the levels of propranolol. Protein binding interactions occur when drugs share the same binding sites on plasma proteins. Drugs like aspirin and warfarin, when bound in excess, can lead to increased free drug concentrations, enhancing the potential for...
01:27Pharmacogenetics of Drug Metabolism: Overview
Genetic polymorphism in drug metabolism is crucial to the inter-individual variability observed in drug responses. Drug metabolism primarily involves the chemical modification of drugs and other xenobiotics to enhance their elimination by increasing their polarity. Two main classes of enzymes mediate this biotransformation process: Phase I enzymes, primarily cytochrome P450s, catalyze oxidation and reduction reactions, while other enzymes, such as esterases, mediate hydrolysis, and Phase II...
01:26Pharmacokinetics: Drug–Food and Drug–Viral Interactions
A drug interaction occurs when the concurrent use of another drug, food, or an external substance alters the pharmacological activity of a drug. This interaction can modify the action of the original drug, affecting its effectiveness and safety.Drug–food interactions are significant as they impact drug absorption, metabolism, and excretion. For example, grapefruit juice is a well-known disruptor of drug metabolism. It inhibits the cytochrome P450 3A4 enzyme, crucial for the metabolism of many...
01:29Pharmacogenomics: Identification of New Drug Targets
Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
01:25Pharmacokinetics: Drug–Drug Interactions
Drug interactions occur when the pharmacological effect of one drug is altered by another substance, either enhancing or diminishing its activity. The drug whose activity is altered is known as the object drug, and the substance causing the alteration is called the agent drug or the precipitant. The net effects of these interactions are mostly undesirable, leading to decreased effectiveness or increased adverse effects. In rare cases, interactions can be beneficial, such as the enhanced...
01:09Bioequivalence of Drugs: Drugs with Multiple Indications
The concept of therapeutic equivalence (TE) in drugs with multiple indications is complex. A generic drug may be therapeutically equivalent to a brand-name product for one specific indication, but this doesn't necessarily mean it's equivalent for all other indications. Evidence of TE in one patient group and bioequivalence shown in healthy volunteers can support—but not confirm—TE for other indications. However, definitive proof requires individual clinical studies for each indication due to...