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

Drug Accumulation During Multiple Dosing: Repetitive IV Injections01:21

Drug Accumulation During Multiple Dosing: Repetitive IV Injections

22
Calculating drug dosage and accumulation in multiple-dose regimens is crucial for achieving therapeutic efficacy while avoiding toxicity. This involves determining the plasma drug concentrations over time to optimize dosing schedules. The principle of superposition is fundamental in this process, allowing for the prediction of drug concentration in plasma following multiple doses based on single-dose data.The principle of superposition asserts that the plasma concentration-time curves from...
22
Measurement of Bioavailability: Pharmacodynamic Methods01:20

Measurement of Bioavailability: Pharmacodynamic Methods

10
Pharmacodynamic methods provide insights into a drug's effects on physiological processes over time and play a crucial role in understanding bioavailability and therapeutic efficacy. These methods can be broadly classified into acute pharmacological and therapeutic response approaches, each with distinct mechanisms and applications.The acute pharmacological response method directly correlates a drug's physiological effects, such as ECG or pupil diameter changes, to its time course in the body.
10
Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response01:15

Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response

148
Circadian rhythms are cyclic changes that are crucial in plasma drug concentrations. Various standard circadian parameters, including core body temperature, heart rate, and other cardiovascular factors, directly impact disease states and the therapeutic response to drug therapy.
The time of drug administration is an important factor to consider, as it can influence the toxic dose of a drug. For example, a study conducted by Prins et al. in 1997 examined the effects of the timing of...
148
Dosage Regimens: Partial Pharmacokinetic Parameters01:01

Dosage Regimens: Partial Pharmacokinetic Parameters

4
It is not uncommon for complete drug pharmacokinetic profiles to remain elusive in pharmacokinetics. This necessitates certain educated assumptions by pharmacokineticists to determine appropriate dosage regimens without comprehensive pharmacokinetic data from animal or human studies. One prevalent assumption is setting the bioavailability factor, denoted as F, to 1 or 100%. This assumption caters to the scenario where a drug doesn't achieve full systemic absorption, resulting in the patient...
4
Drug Accumulation During Multiple Dosing: Intermittent IV Infusions01:24

Drug Accumulation During Multiple Dosing: Intermittent IV Infusions

8
Intermittent intravenous (IV) infusion is a method of drug administration where medications are delivered over short infusion periods followed by intervals of no drug delivery. This approach helps to prevent sustained high drug concentrations in the bloodstream, reducing the risk of adverse effects associated with prolonged exposure. Unlike continuous infusion, steady-state concentrations may not be achieved during a single dosing cycle but can be reached through repeated...
8
Measurement of Bioavailability: Pharmacokinetic Methods01:30

Measurement of Bioavailability: Pharmacokinetic Methods

22
Pharmacokinetics is a vital branch of pharmacology that examines how drugs are absorbed, distributed, metabolized, and excreted by the body. Two key methodologies in pharmacokinetics are plasma drug concentration studies and urinary drug excretion analyses, both of which provide critical insights into a drug's therapeutic efficacy and bioavailability.Plasma Drug Concentration-Time StudiesPlasma drug concentration-time studies involve analyzing blood samples at specific intervals to quantify...
22

You might also read

Related Articles

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

Sort by
Same author

Conceptualizing Experimental Controls Using the Potential Outcomes Framework.

The American statistician·2025
Same author

What Goes into Patient Selection for Lung Cancer Screening? Factors Associated with Clinician Judgments of Suitability for Screening.

American journal of respiratory and critical care medicine·2023
Same author

Factors Associated With Declining Lung Cancer Screening After Discussion With a Physician in a Cohort of US Veterans.

JAMA network open·2022
Same author

Invasive Procedures and Associated Complications After Initial Lung Cancer Screening in a National Cohort of Veterans.

Chest·2022
Same author

Adherence to Follow-up Testing Recommendations in US Veterans Screened for Lung Cancer, 2015-2019.

JAMA network open·2021
Same author

Outcomes of pulmonary vasodilator use in Veterans with pulmonary hypertension associated with left heart disease and lung disease.

Pulmonary circulation·2021

Related Experiment Video

Updated: Oct 4, 2025

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
07:13

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Published on: April 12, 2021

4.5K

Inferring medication adherence from time-varying health measures.

Kristen B Hunter1, Mark E Glickman1, Luis F Campos2

  • 1Department of Statistics, Harvard University, Cambridge, Massachusetts, USA.

Statistics in Medicine
|February 9, 2022
PubMed
Summary

Inferring medication adherence is crucial for chronic disease management. This study introduces a novel method using longitudinal health data to accurately estimate patient adherence rates, improving treatment outcomes.

Keywords:
hypertensionmedication adherencesequential Monte Carlostate-space models

More Related Videos

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation
09:42

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

Published on: November 8, 2013

13.7K
Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
11:21

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

8.3K

Related Experiment Videos

Last Updated: Oct 4, 2025

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
07:13

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

Published on: April 12, 2021

4.5K
Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation
09:42

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

Published on: November 8, 2013

13.7K
Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
11:21

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

8.3K

Area of Science:

  • Biomedical Informatics
  • Health Services Research
  • Clinical Pharmacology

Background:

  • Medication adherence is a significant challenge in chronic disease care, impacting treatment success and patient survival.
  • Current adherence monitoring methods are often resource-intensive or lack accuracy in identifying non-adherent patients.
  • Clinical health measures are more reliably recorded than patient-reported adherence data.

Purpose of the Study:

  • To develop and validate a novel inferential framework to estimate medication adherence rates using longitudinal health measures.
  • To improve the accuracy of identifying patients with poor medication adherence, particularly in chronic disease populations.
  • To provide a resource-efficient method for assessing adherence in clinical settings.

Main Methods:

  • A two-component modular inferential model was developed using electronic medication monitoring data for training.
  • The model predicts adherence behaviors from baseline health and socio-demographic data, and longitudinal health measures from adherence.
  • Markov chain Monte Carlo and sequential Monte Carlo algorithms were employed for parameter simulation and adherence inference.

Main Results:

  • The developed framework successfully inferred medication adherence rates in a cohort of hypertensive patients.
  • The method utilized baseline comorbidities, socio-demographics, and time-varying blood pressure measurements.
  • The approach demonstrated potential for accurate adherence estimation without direct adherence data.

Conclusions:

  • Longitudinal health measures can be effectively leveraged to infer medication adherence rates.
  • This inferential approach offers a promising, accurate, and potentially less resource-intensive alternative to traditional adherence monitoring.
  • Improved adherence estimation can lead to better chronic disease management and patient outcomes.