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

Odds Ratio01:09

Odds Ratio

1.5K
The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
1.5K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

375
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,...
375
Dosage Regimen Designs: Nomograms and Tabulations01:23

Dosage Regimen Designs: Nomograms and Tabulations

147
Nomograms and tabulations are vital tools used by clinicians to design accurate and individualized dosage regimens. These instruments provide a straightforward method for adjusting dosages based on individual patient characteristics, including age, weight, and physiological condition. The foundation of a drug's nomogram is population pharmacokinetic data collected and analyzed using specific models. This data simplifies complex equations, presenting them diagrammatically or tabularly for easy...
147
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

195
Body:Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to...
195
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

150
Body:Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
150
Dosage Regimens: Designs and Approaches01:28

Dosage Regimens: Designs and Approaches

227
Designing a dosage regimen, which refers to the manner of drug administration, is a complex process involving the selection of drug dose, route, and frequency. This process is underpinned by pharmacokinetic parameters derived from tests and population averages. These parameters are then tailored to patient-specific variables such as diagnosis, demographics, and allergy status. Once therapy commences, therapeutic response monitoring is critical and achieved through clinical and physical...
227

You might also read

Related Articles

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

Sort by
Same author

Minimum noninferiority dose for phase I clinical trials with immunotherapy.

Biometrics·2026
Same author

Patient Retreat in Dose Escalation for Phase I Clinical Trials With Rare Diseases.

Statistics in medicine·2026
Same author

Bayesian generalized method of moments applied to pseudo-observations in survival analysis.

Lifetime data analysis·2025
Same author

CFO: Calibration-Free Odds Bayesian Designs for Dose Finding in Clinical Trials.

JCO clinical cancer informatics·2025
Same author

Unit information Dirichlet process prior.

Biometrics·2024
Same author

Fractional accumulative calibration-free odds (f-aCFO) design for delayed toxicity in phase I clinical trials.

Statistics in medicine·2024

Related Experiment Video

Updated: Jan 6, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.5K

Decision Tables for Calibration-Free Odds Design in Phase I Clinical Trials.

Ninghao Zhang1, Guosheng Yin1

  • 1Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, China.

JCO Precision Oncology
|November 20, 2025
PubMed
Summary

This study introduces Excel decision tables for the calibration-free odds (CFO) design, simplifying maximum tolerated dose finding in early-phase clinical trials. These tables enhance usability and reduce complexity for practical trial implementation.

More Related Videos

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.9K
Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

540

Related Experiment Videos

Last Updated: Jan 6, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.5K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.9K
Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

540

Area of Science:

  • Clinical Pharmacology
  • Biostatistics
  • Drug Development

Background:

  • Phase I clinical trials are crucial for assessing drug toxicity and determining the maximum tolerated dose (MTD).
  • Effective dose-finding methods are essential for guiding dose escalation and de-escalation during clinical trials.
  • The calibration-free odds (CFO) design is a highly effective approach for dose finding with superior operating characteristics.

Purpose of the Study:

  • To enhance the practical application of the calibration-free odds (CFO) design in clinical trials.
  • To simplify the implementation of the CFO design by providing accessible decision-making tools.
  • To reduce the operational complexity and statistical burden associated with dose-finding in clinical trials.

Main Methods:

  • Development and presentation of pre-generated decision tables in Excel format for the CFO design.
  • Facilitation of dose movement decisions by referencing cumulative patient data and observed toxicities against these tables.
  • Elimination of the need for additional statistical calculations during trial conduct.

Main Results:

  • The Excel CFO decision tables significantly improve the usability of the CFO design.
  • Implementation of the CFO design becomes straightforward for all trial personnel.
  • Operational complexity in applying the CFO design to real-world clinical trials is substantially reduced.

Conclusions:

  • The Excel CFO decision tables serve as a practical tool to overcome barriers in applying the CFO design.
  • This approach makes advanced dose-finding methodologies more accessible for routine clinical trial use.
  • The tables streamline the process of determining the maximum tolerated dose, enhancing efficiency in early drug development.