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

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

159
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
159
Randomized Experiments01:13

Randomized Experiments

7.1K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
7.1K
Blinding01:11

Blinding

2.5K
Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control trial or RCT. It reduces the bias that affects the results. In an RCT, blinding is used in the form of a placebo. A placebo effect occurs when untreated subjects falsely believe they have received the treatment and report improved symptoms. A placebo or a dummy treatment is administered to subjects to negate the bias caused by such an effect.
2.5K
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

144
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
144
Clinical Trials: Overview01:11

Clinical Trials: Overview

3.1K
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...
3.1K
Clinical Trials01:16

Clinical Trials

7.0K
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...
7.0K

You might also read

Related Articles

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

Sort by
Same author

Predicting unfavorable tuberculosis outcomes using machine learning: a prospective cohort.

Tropical medicine and health·2026
Same author

Study on the safety evaluation of latent tuberculosis treatment in high‑risk groups for tuberculosis development: Study protocol for a multi‑center prospective observational cohort study in Korea (STEP-TB).

PloS one·2026
Same author

Asymptomatic tuberculosis detected in health screening predicts favourable outcome.

ERJ open research·2026
Same author

Factors associated with extended treatment duration in patients with drug-susceptible pulmonary tuberculosis: a prospective multicentre cohort study in South Korea.

BMC infectious diseases·2026
Same author

Association between reduced kidney function and tuberculosis treatment outcomes.

BMC infectious diseases·2026
Same author

Impact of mass resident physician resignation on inpatient mortality and admissions in Korea.

Public health·2026

Related Experiment Video

Updated: Aug 24, 2025

Preparation of Peripheral Blood Mononuclear Cell Pellets and Plasma from a Single Blood Draw at Clinical Trial Sites for Biomarker Analysis
07:40

Preparation of Peripheral Blood Mononuclear Cell Pellets and Plasma from a Single Blood Draw at Clinical Trial Sites for Biomarker Analysis

Published on: March 20, 2021

17.1K

Challenges and opportunities in biomarker-driven trials: adaptive randomization.

Yeonhee Park1

  • 1Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA.

Annals of Translational Medicine
|October 21, 2022
PubMed
Summary

Biomarker-driven adaptive randomization can optimize treatment allocation in clinical trials. However, prognostic biomarkers may inflate type I error rates, requiring careful management for accurate results.

Keywords:
Adaptive randomizationbiomarkersclinical trialsgroup sequential designpersonalized medicine

More Related Videos

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

14.6K
Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
05:19

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

Published on: July 7, 2023

2.4K

Related Experiment Videos

Last Updated: Aug 24, 2025

Preparation of Peripheral Blood Mononuclear Cell Pellets and Plasma from a Single Blood Draw at Clinical Trial Sites for Biomarker Analysis
07:40

Preparation of Peripheral Blood Mononuclear Cell Pellets and Plasma from a Single Blood Draw at Clinical Trial Sites for Biomarker Analysis

Published on: March 20, 2021

17.1K
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

14.6K
Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
05:19

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

Published on: July 7, 2023

2.4K

Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Precision Medicine

Background:

  • Precision medicine relies on molecular profiling to tailor treatments.
  • Biomarkers are crucial for identifying patient subgroups likely to benefit from specific therapies.
  • Integrating biomarkers into clinical trials enhances efficiency and understanding of treatment relationships.

Purpose of the Study:

  • To investigate the incorporation of biomarkers into adaptive randomization for clinical trials.
  • To optimize treatment allocation by identifying patients who respond better to specific treatments.
  • To compare the performance of biomarker-driven randomization against existing methods.

Main Methods:

  • Utilized covariate-adjusted response-adaptive randomization for biomarker incorporation.
  • Compared biomarker-driven randomization with fixed randomization and non-biomarker response-adaptive randomization.
  • Evaluated performance under group sequential designs with early stopping for superiority and futility.

Main Results:

  • Biomarker-driven randomization aims to improve treatment allocation efficiency.
  • Prognostic biomarkers can potentially inflate the overall type I error rate.
  • Simulation studies explored various scenarios to assess the impact of biomarker integration.

Conclusions:

  • Biomarker-driven adaptive randomization offers a promising approach for precision medicine trials.
  • Strategies are needed to mitigate the risk of inflated type I error rates due to prognostic biomarkers.
  • Careful consideration and adjustments are essential for maintaining statistical validity.