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

Decision Making: P-value Method01:09

Decision Making: P-value Method

5.6K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.6K
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

4.1K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
4.1K
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

118
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
118
Factorial Design02:01

Factorial Design

13.1K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
13.1K
Study Design in Statistics01:15

Study Design in Statistics

8.3K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
8.3K
Group Design02:01

Group Design

9.0K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
9.0K

You might also read

Related Articles

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

Sort by
Same author

Statistical analysis plan considerations for autologous cell and cell-based gene therapy clinical trials.

Journal of biopharmaceutical statistics·2026
Same author

Overview of dose-finding designs and trials in cell and gene therapies.

Journal of biopharmaceutical statistics·2026
Same author

Testing rates and outcomes in <i>Clostridioides difficile</i> infection between REM (racially and ethnically minoritized) and non-REM patients.

Infection control and hospital epidemiology·2026
Same author

Exploiting vitamin C as a prooxidant to activate ROS-responsive prodrugs for potent and selective tumor killing.

Redox biology·2026
Same author

Pivotal trial design considerations for new and next generation cell and gene therapies.

Journal of biopharmaceutical statistics·2026
Same author

Trans-Phylum Single Cell Orthology Reveals Conserved Ovarian Cell States Between Sea Urchin and Human.

Genome biology and evolution·2026

Related Experiment Video

Updated: Aug 8, 2025

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

6.1K

Bayesian optimal phase II designs with dual-criterion decision making.

Yujie Zhao1, Daniel Li2, Rong Liu2

  • 1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.

Pharmaceutical Statistics
|March 5, 2023
PubMed
Summary

The Bayesian optimal phase II trial design with dual-criterion decision making (BOP2-DC) improves drug development by integrating statistical significance and clinical relevance. This approach enables nuanced go/consider/no-go decisions for more effective clinical trial progression.

Keywords:
Bayesian adaptive designgo/consider/no-go decisionoptimal designphase II trials

More Related Videos

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.2K
The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
08:24

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

Published on: August 25, 2023

779

Related Experiment Videos

Last Updated: Aug 8, 2025

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

6.1K
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.2K
The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
08:24

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

Published on: August 25, 2023

779

Area of Science:

  • Clinical Trials
  • Biostatistics
  • Drug Development

Background:

  • Conventional phase II trial designs rely on hypothesis testing for go/no-go decisions.
  • Statistical significance alone may not confirm sufficient clinical effectiveness for phase III trials.

Purpose of the Study:

  • To introduce the Bayesian optimal phase II trial design with dual-criterion decision making (BOP2-DC).
  • To enhance decision-making in phase II trials by incorporating both statistical and clinical significance.

Main Methods:

  • BOP2-DC utilizes posterior probabilities for statistical and clinical significance.
  • It supports go/consider/no-go decisions, moving beyond binary outcomes.
  • The design accommodates diverse endpoints (binary, continuous, time-to-event) and trial types (single-arm, randomized).

Main Results:

  • Simulation studies demonstrate desirable operating characteristics for the BOP2-DC design.
  • The decision rule is optimized to maximize successful drug progression or minimize sample size for futile treatments.

Conclusions:

  • BOP2-DC offers a flexible and robust framework for phase II trial decision-making.
  • Integrating clinical relevance alongside statistical significance leads to more informed progression to phase III trials.