Related Experiment Video
Updated: Apr 7, 2026
11:15
Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations
Published on: July 24, 2021
5.7K
A two-dimensional biased coin design for dual-agent dose-finding trials
1Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA zcs@umich.edu.
Clinical Trials (London, England)
|July 12, 2015
Summary
This study introduces a new nonparametric design for Phase I clinical trials to find the best combination of two cancer drugs. The adaptive biased coin design improves patient safety and accurately identifies the maximum tolerated combination.
Area of Science:
- Clinical Trial Design
- Pharmacometrics
- Biostatistics
Background:
- Limited efficacy of single agents necessitates combination therapies.
- Growing need for Phase I clinical trial designs to identify optimal drug combinations.
- Existing parametric designs for combination trials may be over- or under-parameterized.
Purpose of the Study:
- To develop a novel, easily understandable, and implementable nonparametric approach for dual-agent dose-finding trials.
- To address limitations of existing parametric designs in combination therapy trials.
Main Methods:
- Proposed a two-stage adaptive biased coin design for dual-agent dose-finding.
- Extended single-agent trial methods to combination settings.
- Modified the biased coin design for application in two distinct trial stages.
Main Results:
- The proposed nonparametric design performed well in simulations across various scenarios.
- Successfully identified the maximum tolerated combination and allocated patients effectively.
- Outperformed competing parametric approaches in key operating characteristics.
Conclusions:
- The design offers favorable statistical properties and promotes patient safety.
- Requires careful consideration of stopping rules and sample size distribution between stages.
- Efficacy is not used in dose assignment or defining the maximum tolerated combination.
Related Concept Videos
01:22Bias
8.0K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
8.0K
01:20Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs
375
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 subjects...
375
01:15Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs
392
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...
392
01:16Crossover Experiments
4.7K
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.
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.
4.7K
01:28Dosage Regimens: Designs and Approaches
483
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...
483
01:23Dosage Regimen Designs: Nomograms and Tabulations
305
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...
305