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

Model Approaches for Pharmacokinetic Data: Compartment Models

Model Approaches for Pharmacokinetic Data: Compartment Models

Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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...

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This relationship...

Therapeutic Drug Monitoring: Overview and Classification

Therapeutic Drug Monitoring: Overview and Classification

Therapeutic Drug Monitoring (TDM) is a clinical practice that measures specific drug levels in a patient's blood at designated intervals to ensure the drug concentration stays within a therapeutic range. This monitoring is crucial for optimizing individual dosage regimens, enhancing therapeutic efficacy, and minimizing drug-related toxicity. TDM is vital for drugs with narrow therapeutic windows, significant variability in pharmacokinetics, and a clear correlation between plasma levels and...

Longitudinal Research

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...

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,...

You might also read

Related Articles

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

Sort by

Same author

Prescriber-recorded indications for antipsychotic use in children and adolescents in Spain, 2015-2023: a population-based, real-world study.

European child & adolescent psychiatry·2025

Same author

APPRAISE: A Tool for Appraising Potential for Bias in Real-World Evidence Studies on Medication Effectiveness or Safety.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research·2025

Same author

Contemporary pharmacological management of patients after hip fracture: a population-based cohort of over 120,000 patients in Spain.

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA·2025

Same author

A population-based cohort to evaluate drug safety during pregnancy (PREGVAL): rationale, design, and baseline characteristics.

European journal of epidemiology·2025

Same author

Incidence of Conjunctivitis and Keratitis Among Individuals with Moderate-to-Severe Atopic Dermatitis Treated with Dupilumab in the United States: a Cohort Study in Routine Care Based on Healthcare Claims.

Dermatology and therapy·2025

Same author

Association of glucagon-like peptide-1 receptor agonists with acute pancreatitis and biliary disease in individuals with diabetes and obesity: a propensity-weighted, population-based cohort study.

Gaceta sanitaria·2025

Search research articles

Related Experiment Video

Updated: May 11, 2026

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Published on: November 8, 2013

Group-based trajectory models: a new approach to classifying and predicting long-term medication adherence.

Jessica M Franklin¹, William H Shrank, Juliana Pakes

¹Department of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02120, USA. jmfranklin@partners.org

|May 21, 2013

Summary

Group-based trajectory models effectively classify long-term medication adherence, outperforming traditional methods like proportion of days covered (PDC). This novel approach aids in targeting adherence interventions more efficiently.

Related Experiment Videos

Last Updated: May 11, 2026

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Published on: November 8, 2013

Area of Science:

Pharmacoeconomics
Health Services Research
Biostatistics

Background:

Accurate classification of medication adherence is crucial for effective intervention targeting.
Traditional adherence metrics may not fully capture long-term patient behavior patterns.

Purpose of the Study:

To evaluate group-based trajectory models as a novel method for classifying long-term medication adherence.
To compare the performance of trajectory models against traditional adherence summary measures.

Main Methods:

Utilized prescription claims data for 264,789 statin initiators over 15 months.
Compared group-based trajectory models (2-6 groups) with proportion of days covered (PDC) for adherence summarization.
Assessed prediction accuracy of adherence using patient characteristics for both methods.

Main Results:

The 6-group trajectory model provided a superior summary of long-term adherence (C=0.938) compared to PDC (C=0.881).
Adherence prediction accuracy was comparable whether classified by trajectory model or PDC.
Covariates similarly predicted adherence regardless of classification method.

Conclusions:

Group-based trajectory models offer a more comprehensive summary of adherence patterns than traditional methods.
These models can enhance the targeting of adherence improvement interventions.
Trajectory models may help control for confounding factors like health-seeking behavior.