Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

858
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
858
Nonlinear Pharmacokinetics: Overview01:19

Nonlinear Pharmacokinetics: Overview

487
Nonlinear or dose-dependent pharmacokinetics is a phenomenon that occurs when the pharmacokinetic parameters of certain drugs deviate from linear pharmacokinetics at higher doses. These drugs do not follow the expected first-order kinetics, where the rate of drug elimination is directly proportional to the drug concentration. Instead, they exhibit a nonlinear relationship, which can be attributed to several factors.
Nonlinearity can arise due to the saturation of plasma protein-binding or...
487
Biopharmaceutics and Pharmacokinetics: Overview01:28

Biopharmaceutics and Pharmacokinetics: Overview

2.2K
Understanding drugs, drug products, and their performance in pharmaceutical science is pivotal. Drugs, whether simple molecules or complex compounds, are designed to interact with the body's biological systems to diagnose, treat, or prevent diseases. Drug products include various delivery systems such as tablets, capsules, injections, and inhalers. The performance of these drug products is gauged by their ability to deliver the active ingredient to the desired site of action at the...
2.2K
Pharmacokinetics: Overview01:10

Pharmacokinetics: Overview

6.6K
Pharmacokinetics is a scientific discipline that focuses on the journey of a drug within the body, encompassing four key stages: absorption, distribution, metabolism, and elimination. The first stage, absorption, involves the drug's transfer into the bloodstream. Several factors dictate the extent and speed of this process. For example, the liver often metabolizes oral drugs before they reach systemic circulation, leading to only partial absorption. In contrast, intravenous (IV)...
6.6K
Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs01:21

Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs

1.7K
The fundamental mathematical principles, such as calculus and graphs, play crucial roles in analyzing drug movement and determining pharmacokinetic parameters. Differential calculus examines rates of change and helps to determine the dissolution rate of drugs in biofluids, as well as how drug concentrations change over time. For instance, it can help calculate the rate of elimination of a drug from the body based on its concentration-time profile.
On the other hand, integral calculus focuses on...
1.7K
Pharmacodynamics: Overview and Principles01:21

Pharmacodynamics: Overview and Principles

1.4K
Pharmacodynamics is a scientific field that delves into drugs' intricate biochemical, cellular, and physiological effects on the human body. The study of pharmacodynamics helps us understand how drugs interact with the body and elicit various responses.
Most drugs' effects result from their interactions with drug receptors or targets within the body. These interactions trigger specific responses at the cellular or systemic level. Drug receptors can be found on the surfaces of cells or...
1.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Goals and strategies for the indexing of publication types and study designs.

Database : the journal of biological databases and curation·2026
Same author

The combined use of natural language processing and electronic health records data to identify historical tolerances of β-lactams and promote clinician confidence in future use.

Health systems (Basingstoke, England)·2026
Same author

KG-Microbe - Building Modular and Scalable Knowledge Graphs for Microbiome and Microbial Sciences.

GigaScience·2026
Same author

Predicting risk of unplanned subsequent knee surgery following ACL reconstruction.

BMC musculoskeletal disorders·2026
Same author

SPIRIT-CONSORT-ELM: Element-Level Assessment of Randomized Controlled Trial Reporting Using Large Language Models.

medRxiv : the preprint server for health sciences·2026
Same author

Assessing Multimodal AI for Visual Information Extraction of Pharmacology.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science·2026

Related Experiment Video

Updated: Aug 6, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.7K

Developing a Knowledge Graph for Pharmacokinetic Natural Product-Drug Interactions.

Sanya B Taneja1, Tiffany J Callahan2, Mary F Paine3

  • 1Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA 15206, USA.

Journal of Biomedical Informatics
|March 18, 2023
PubMed
Summary

Researchers created NP-KG, a novel knowledge graph, to computationally identify natural product-drug interactions. This tool helps understand pharmacokinetic interactions and prevent adverse events from botanical and drug co-consumption.

Keywords:
Biomedical ontologyInteractionsKnowledge graphKnowledge representationLiterature-based discoveryNatural productsPharmacokinetics

More Related Videos

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

406
A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
07:40

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

4.2K

Related Experiment Videos

Last Updated: Aug 6, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.7K
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

406
A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
07:40

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

4.2K

Area of Science:

  • Biomedical Informatics
  • Pharmacology
  • Computational Biology

Background:

  • Pharmacokinetic natural product-drug interactions (NPDIs) are increasing due to widespread natural product use.
  • Understanding NPDI mechanisms is crucial for preventing adverse drug events.
  • Computational approaches for NPDIs are novel, unlike established drug-drug interaction tools.

Purpose of the Study:

  • To construct NP-KG, a knowledge graph for discovering mechanistic explanations of pharmacokinetic NPDIs.
  • To computationally investigate potential NPDIs involving natural products.
  • To provide a tool for guiding scientific research on NPDIs.

Main Methods:

  • Developed a large-scale, heterogeneous knowledge graph (KG) integrating biomedical ontologies, linked data, and scientific literature.
  • Utilized SemRep and Integrated Network and Dynamic Reasoning Assembler for semantic relation extraction from literature on green tea and kratom.
  • Integrated literature-based graphs into an ontology-grounded KG to create NP-KG, evaluated via path searches and meta-path discovery.

Main Results:

  • The NP-KG contains 745,512 nodes and 7,249,576 edges.
  • Evaluation showed congruent information for 38.98% (green tea) and 50% (kratom) of interactions, with some contradictory findings.
  • Identified potential pharmacokinetic mechanisms for known interactions, such as green tea-raloxifene and kratom-midazolam.

Conclusions:

  • NP-KG is the first KG to integrate biomedical ontologies with scientific literature for natural product-focused research.
  • Demonstrated NP-KG's utility in identifying pharmacokinetic interactions mediated by enzymes and transporters.
  • Future work includes enhancing NP-KG with context, contradiction analysis, and embedding methods. NP-KG is publicly available.