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

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.3K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.3K
Clinical Trials: Overview01:11

Clinical Trials: Overview

4.5K
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...
4.5K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

373
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,...
373
Clinical Trials01:16

Clinical Trials

10.1K
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...
10.1K
Biostatistics: Overview01:20

Biostatistics: Overview

681
Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
681
Bioequivalence Data: Statistical Interpretation01:16

Bioequivalence Data: Statistical Interpretation

173
Body:The statistical interpretation of bioequivalence data is a significant aspect of pharmaceutical research. Bioequivalence refers to the absence of any significant difference in the rate and extent to which the active ingredient in pharmaceutical products becomes available at the site of drug action when administered at the same molar dose under similar conditions. This helps determine if different drug products have similar absorption rates, ensuring their interchangeability.Statistical...
173

You might also read

Related Articles

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

Sort by
Same author

Effect of Intraoperative Epidural Steroid in Early Outcomes After Full-Endoscopic Lumbar Discectomy - A Randomized Controlled Trial.

Global spine journal·2026
Same author

Enabling AI to Drive Innovation and Precision across Oncology R&D.

Cancer discovery·2026
Same author

Lumbar Disc Herniation Resorption: When and How Does It Occur?

Neurospine·2026
Same author

Learning From the Uncommon in Common Practice: A Case Report on Metamizole-Induced Agranulocytosis.

Cureus·2026
Same author

Extracorporeal Blood Purification (HA-380) in Rhabdomyolysis-Induced Acute Kidney Injury: A Successful Outcome.

European journal of case reports in internal medicine·2026
Same author

Generative AI in pharmaceutical R&D: From large language models to AI agents to regulation.

Drug discovery today·2026

Related Experiment Video

Updated: Jan 5, 2026

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

7.9K

Biomarker data visualisation for decision making in clinical trials.

Alan Davies1, Marisa Cunha2, Kamilla Kopec-Harding3

  • 1School of Health Sciences, University of Manchester, Manchester, UK.

International Journal of Medical Informatics
|October 23, 2019
PubMed
Summary

Visualizing biomarker data in clinical trials aids decision-making. Improving trust in these visualizations requires clear access to underlying data, enhancing clinical trial processes.

Keywords:
BiomarkersClinical trialsInterviewsProvenanceThematic analysisTrustVisualizations

More Related Videos

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.1K
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

9.4K

Related Experiment Videos

Last Updated: Jan 5, 2026

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

7.9K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.1K
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

9.4K

Area of Science:

  • Clinical Trials
  • Biomarker Data Visualization
  • Decision Support Systems

Background:

  • Effective visualization of biomarker data is crucial for informed decision-making in clinical trials.
  • Current methods for accessing underlying data for visualizations lack standardization.

Purpose of the Study:

  • To explore the utilization of biomarker data visualizations in clinical trials.
  • To identify challenges and propose enhancements for visualization processes in clinical decision-making.

Main Methods:

  • Conducted semi-structured interviews with 18 professionals in clinical trial visualization.
  • Employed inductive thematic analysis to interpret interview data.

Main Results:

  • Identified six key themes regarding visualization use, data understanding, purpose, and properties.
  • Participant trust in visualizations is contingent on accessible underlying data, which is currently not standardized.

Conclusions:

  • Enhancing biomarker visualizations with data provenance information can bolster user trust.
  • Improved trust through data provenance can streamline decision-making in clinical trials.