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: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

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 assumptions,...
Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs01:21

Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs

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...
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

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...

You might also read

Related Articles

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

Sort by
Same author

Navigating the artificial intelligence landscape in trauma, critical care and emergency general surgery: insights from the American Association for the Surgery of Trauma (AAST) 2025 Annual Meeting Panel Discussion.

Trauma surgery & acute care open·2026
Same author

"Catch My Drift?"

Critical care medicine·2026
Same author

The authors reply.

Critical care medicine·2025
Same author

Effect of Monetary Incentives on Peer Review Acceptance and Completion: A Quasi-Randomized Interventional Trial: Erratum.

Critical care medicine·2025
Same author

The authors reply.

Critical care medicine·2025
Same author

Fair Use of Augmented Intelligence and Artificial Intelligence in the Preparation and Review of Submissions to the Society of Critical Care Medicine Journals: Critical Care Medicine, Pediatric Critical Care Medicine, and Critical Care Explorations.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies·2025
Same journal

The authors reply.

Critical care medicine·2026
Same journal

Attracting Emergency Medicine Graduates to Surgical Critical Care Training Programs.

Critical care medicine·2026
Same journal

The authors reply.

Critical care medicine·2026
Same journal

Beyond a Snapshot: Tracking Family Prognostic Expectations in the ICU.

Critical care medicine·2026
Same journal

The authors reply.

Critical care medicine·2026
Same journal

Plasma Levels of Soluble ST2 Reflect Extrapulmonary Organ Dysfunction and Predict Outcomes in Acute Respiratory Failure: Beware of Potential Confounders.

Critical care medicine·2026
See all related articles

Related Experiment Video

Updated: Jun 25, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

The digital patient: predicting physiologic dynamics with mathematical models

Timothy G Buchman

    Critical Care Medicine
    |February 25, 2009
    PubMed
    Summary

    No abstract available in PubMed .

    More Related Videos

    In Silico Clinical Trials for Cardiovascular Disease
    09:09

    In Silico Clinical Trials for Cardiovascular Disease

    Published on: May 27, 2022

    Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
    12:09

    Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

    Published on: January 8, 2013

    Related Experiment Videos

    Last Updated: Jun 25, 2026

    Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
    10:28

    Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

    Published on: July 24, 2019

    In Silico Clinical Trials for Cardiovascular Disease
    09:09

    In Silico Clinical Trials for Cardiovascular Disease

    Published on: May 27, 2022

    Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
    12:09

    Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

    Published on: January 8, 2013