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

Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

107
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
107
Clearance Models: Physiological Models01:09

Clearance Models: Physiological Models

120
Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
The organ's clearance rate depends on the blood flow to the organ and the extraction ratio (E). The extraction ratio describes the organ's...
120
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

252
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
252
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

85
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
85
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

158
Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
158
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

147
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
147

You might also read

Related Articles

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

Sort by
Same author

A Theoretical Understanding of both Activity and Stability Promotion of NiFe-Based OER Catalysts via 3d-2p-4f Orbital Hybridization.

The journal of physical chemistry letters·2026
Same author

Full-Body AI Agent: A Perspective on Multi-Scale Collaborative AI for Systemic Biology and Precision Medicine.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Chatbot Usability Scale in Chinese Users: Cross-Cultural Adaptation and Validation Study.

JMIR human factors·2026
Same author

The Influence Pathway of the Burden on Caregivers of Children With Congenital Ear Malformations: An Analysis of the Mediating Effects of Social Support and Coping Mechanisms.

The Journal of craniofacial surgery·2026
Same author

A hierarchical Bayesian framework for inferring mitochondrial clonal selection from single-cell data.

Research square·2026
Same author

Development and evaluation of an large language model-integrated chatbot intervention for physical activity habit formation in adults with prehypertension.

Digital health·2026
Same journal

MetaboNet-Bench: A Multi-modal Benchmark for Glucose Forecasting in Type 1 Diabetes.

ArXiv·2026
Same journal

A Positron Range Correction with Texture Preservation Framework in PET Imaging.

ArXiv·2026
Same journal

Automated optimization of force field parameters against ensemble-averaged measurements with Bayesian Inference of Conformational Populations.

ArXiv·2026
Same journal

Droplet Fusion as a Relaxation Process: Comparison with Shape Recovery of Newtonian and Viscoelastic Droplets.

ArXiv·2026
Same journal

Ridge-filter crosstalk in conformal proton FLASH planning: dependence on beamlet pitch and iterative mitigation.

ArXiv·2026
Same journal

Electrochemical DNA Hairpin Sensors for Differentiating Small Molecule Intercalation from Minor Groove Binding.

ArXiv·2026
See all related articles

Related Experiment Video

Updated: Sep 9, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.2K

A Multi-Layered Framework for Modeling Human Biology: From Basic AI Agents to a Full-Body AI Agent.

Aoqi Wang1, Jiajia Liu2, Jianguo Wen2

  • 1West China Biomedical Big Data Centre, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, PR China.

Arxiv
|September 5, 2025
PubMed
Summary
This summary is machine-generated.

The Full-Body AI Agent simulates human body processes across all biological levels for disease research and personalized medicine. It aids in understanding metastasis and drug development by integrating multi-scale data for predictive modeling.

More Related Videos

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

603
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

565

Related Experiment Videos

Last Updated: Sep 9, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.2K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

603
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

565

Area of Science:

  • Computational Biology
  • Systems Biology
  • Artificial Intelligence in Medicine

Background:

  • Understanding complex human physiological and pathological processes requires multi-level biological integration.
  • Current models often lack the ability to connect molecular changes to systemic outcomes.
  • Predictive modeling for disease progression and therapeutic response remains a significant challenge.

Purpose of the Study:

  • To introduce the Full-Body AI Agent, a comprehensive system for simulating, analyzing, and optimizing human body dynamics.
  • To demonstrate the framework's utility through specialized agents for metastasis and drug development.
  • To advance understanding of disease mechanisms and support personalized medicine.

Main Methods:

  • Integration of computational models, machine learning, and experimental platforms.
  • Multi-scale analysis from molecules to entire body systems.
  • Development of specialized AI agents for metastasis scoring and system-level drug development.

Main Results:

  • The metastasis AI Agent characterizes tumor progression by integrating molecular, cellular, and systemic signals.
  • The drug AI Agent guides preclinical evaluations with full-body physiological constraints for predictive efficacy and toxicity.
  • Demonstrated potential for cross-scale reasoning to address complex biomedical challenges.

Conclusions:

  • The Full-Body AI Agent framework enables integrated, multi-level analysis of biological systems.
  • Specialized agents show promise in advancing cancer research and drug development.
  • This approach enhances predictive modeling for improved healthcare outcomes.