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Related Experiment Video

Updated: Apr 16, 2026

Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations

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Published on: July 24, 2021

Experimental design and statistical analysis for three-drug combination studies.

Hong-Bin Fang¹, Xuerong Chen², Xin-Yan Pei³

¹1 Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University Medical Center, Washington, USA.

Statistical Methods in Medical Research

|March 7, 2015

Summary

This study introduces novel methods for analyzing high-dimensional drug combinations, crucial for developing effective cancer and HIV therapies. It presents the first three-drug combination analysis on a full dose-response surface, advancing combination drug discovery.

Keywords:

Drug combination F-test dose effect experimental design interaction index maximum power design nonparametric estimation synergism

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Area of Science:

Pharmacology and Biostatistics
Computational Biology
Drug Discovery

Background:

Multidrug combinations are vital for treating complex diseases like cancer and HIV.
Current experimental designs for drug combinations are suboptimal, often reducing dimensionality by fixing drug doses.
There is a critical need for methods to analyze high-dimensional (three or more drugs) combinations directly.

Purpose of the Study:

To develop experimental design and analysis methods for studying multidrug combinations, particularly high-dimensional ones.
To address the complexity of three-drug combinations and their dose-response surfaces.
To provide methods for dose finding and sample size determination for detecting drug interactions.

Main Methods:

Developed dose-finding and sample size methods for detecting departures from additivity across common dose-response curve classes (linear, log-linear).
Proposed a nonparametric model using B-spline approximation to estimate the interaction index surface.
Derived asymptotic properties for the nonparametric interaction index estimation model.

Main Results:

Successfully designed and analyzed a three-drug combination study (PD184, HA14-1, CEP3891) against myeloma H929 cell line.
This represents the first study to analyze a three-drug combination on its complete 4D dose-response surface.
The developed methods enable robust analysis of complex drug interactions.

Conclusions:

The developed methods overcome limitations of existing approaches for high-dimensional drug combination studies.
This work facilitates more accurate and comprehensive evaluation of synergistic, additive, or antagonistic drug effects.
Enables accelerated development of novel combination therapies for complex diseases.