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

Crossover Experiments01:16

Crossover Experiments

2.9K
Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
2.9K
Clinical Trials01:16

Clinical Trials

6.8K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
6.8K
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

130
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...
130
Data Collection by Experiments01:13

Data Collection by Experiments

24.3K
Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...
24.3K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

96
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...
96
Clinical Trials: Overview01:11

Clinical Trials: Overview

3.0K
Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
3.0K

You might also read

Related Articles

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

Sort by
Same author

Compensatory Smoking With Very Low Nicotine Content Cigarettes: A Systematic Review and Meta-Analysis.

JAMA network open·2026
Same author

Outcomes for persons with triple-class resistant HIV and a history of virologic failure.

International journal of antimicrobial agents·2026
Same author

Meningococcal B Vaccine to Prevent <i>Neisseria gonorrhoeae</i> Infection.

The New England journal of medicine·2026
Same author

CD4+ cell count trends after common cancers in people with HIV: a multicohort collaboration.

AIDS (London, England)·2026
Same author

HIV cascade, key indicators, and other epidemiological metrics in Australia (2004-2023): a retrospective analysis.

The Lancet regional health. Western Pacific·2026
Same author

Association of travel nursing with quality outcomes in hospitalized patients.

The American journal of managed care·2026

Related Experiment Video

Updated: Jul 16, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.5K

Semi-supervised mixture multi-source exchangeability model for leveraging real-world data in clinical trials.

Lillian M F Haine1, Thomas A Murry1, Raquel Nahra2

  • 1Division of Biostatistics, University of Minnesota, Minneapolis, MN, 55414, USA.

Biostatistics (Oxford, England)
|September 12, 2023
PubMed
Summary

This study introduces a novel Bayesian method to integrate real-world data (RWD) into clinical trials, improving efficiency and reducing bias. The approach effectively borrows information when data sources align and mitigates risks when they differ.

Keywords:
Bayesian model averagingCausal inferenceInfluenzaPropensity scoresReal-world data

More Related Videos

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K
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

267

Related Experiment Videos

Last Updated: Jul 16, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.5K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K
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

267

Area of Science:

  • Biostatistics
  • Clinical Trial Methodology
  • Real-World Evidence

Background:

  • Traditional clinical trials face challenges of being slow, inefficient, and costly.
  • Existing methods for external data integration primarily use data from prior trials, overlooking valuable real-world data (RWD).

Purpose of the Study:

  • To propose a flexible, two-step Bayesian approach for incorporating RWD into randomized controlled trial (RCT) analyses.
  • To enhance trial efficiency and statistical power by leveraging RWD while mitigating potential biases.

Main Methods:

  • A semi-supervised mixture (SS-MIX) multisource exchangeability model (MEM) was developed.
  • The approach involves a two-step Bayesian process: SS-MIX on propensity scores and MEM to manage data differences.
  • The method selectively borrows information, avoiding bias when trial and RWD differ on covariates.

Main Results:

  • Simulation studies demonstrated that the proposed approach efficiently borrows data when trial and RWD are consistent.
  • The method effectively mitigates bias arising from differences in measured or unmeasured covariates between trial and RWD.
  • An application to an influenza trial showed successful supplementation of subgroup analysis using external observational data.

Conclusions:

  • The SS-MIX MEM offers a robust strategy for integrating RWD into RCTs.
  • This approach enhances the efficiency of clinical trials and improves the reliability of results, especially when dealing with heterogeneous data sources.
  • The methodology provides a valuable tool for maximizing the utility of RWD in pharmaceutical research and clinical decision-making.