Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Pharmacokinetic Models: Overview

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: Overview

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...

Analysis of Population Pharmacokinetic Data

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...

Pharmacokinetic Models: Comparison and Selection Criterion

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.

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).

You might also read

Related Articles

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

Sort by

Same author

Measuring performance in cancer services during COVID-19 and beyond: a novel case throughput metric using NHS Cancer Waiting Times data.

Journal of public health (Oxford, England)·2026

Same author

The health and health inequalities impact of a place-based community wealth initiative, a mixed-methods study.

Public health research (Southampton, England)·2026

Same author

COVID-19's disruptions to cancer care pathways and widening of health inequalities in the UK: a systematic review.

BMC health services research·2026

Same author

Austerity and waiting times: Evidence on reproductive health care delays among young millennials in deprived areas.

Public health·2025

Same author

Joint effects of ill-health, health shocks and social protection on the intensive margin of labour supply: evidence from Malawi.

Health economics review·2024

Same author

Correction: Deficits and opportunities, pivots and shifts for scaling-up voluntary medical male circumcision in Uganda: a qualitative reflexive thematic analysis study.

BMC public health·2024

Search research articles

Related Experiment Video

Updated: May 19, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

Overview of pharmacoeconomic modelling methods.

Zanfina Ademi¹, Hansoo Kim, Ella Zomer

¹Melbourne EpiCentre, Department of Medicine (Royal Melbourne Hospital), The University of Melbourne, Melbourne, Victoria, Australia. zademi@unimelb.edu.au

British Journal of Clinical Pharmacology

|August 14, 2012

Summary

Pharmacoeconomics is crucial for managing rising healthcare expenses, yet clinicians often lack knowledge of its methods. This review introduces key pharmacoeconomic modeling techniques and guides appraisal of published analyses.

More Related Videos

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Published on: September 26, 2025

Related Experiment Videos

Last Updated: May 19, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Published on: September 26, 2025

Area of Science:

Health Economics
Clinical Pharmacy
Health Services Research

Background:

Rising healthcare costs necessitate efficient resource allocation.
Pharmacoeconomic evaluations are vital for informed decision-making.
Clinicians require accessible knowledge of pharmacoeconomic methodologies.

Purpose of the Study:

To provide an introductory overview of pharmacoeconomic modeling.
To explain common methods like decision analysis and Markov modeling.
To offer guidance on critically appraising published pharmacoeconomic studies.

Main Methods:

Review of established pharmacoeconomic modeling techniques.
Explanation of decision analysis and Markov models.
Description of discounting and Monte Carlo simulation for uncertainty analysis.

Main Results:

Common pharmacoeconomic modeling methods include decision analysis, Markov modeling, discounting, and Monte Carlo simulation.
Understanding these methods is essential for interpreting study results.
Appraisal requires familiarity with the underlying modeling approaches.

Conclusions:

Pharmacoeconomic modeling knowledge is limited but essential for clinicians.
This review serves as a foundational guide to key methods.
Effective appraisal of pharmacoeconomic analyses is achievable with proper understanding.