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A mapping-based universal Kriging model for order-of-addition experiments in drug combination studies

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  • Xiao, Qian
  • Xu, Hongquan

Abstract

In modern pharmaceutical studies, treatments may include several drugs added sequentially, and the drugs’ order-of-addition can have significant impacts on their efficacy. In practice, experiments enumerating all possible drug sequences are often not affordable, and appropriate statistical models which can accurately predict all cases using only a small number of experimental trials are required. A novel mapping-based universal Kriging (MUK) model and its simplified variant are proposed for analyzing such order-of-addition experiments with blocking. They can provide accurate predictions and have robust performances under various experimental designs. The MUK model can also incorporate available domain knowledge to enhance its interpretation. The superiority of the proposed methods is illustrated via a real five-drug experiment on lymphoma and two simulation examples.

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  • Xiao, Qian & Xu, Hongquan, 2021. "A mapping-based universal Kriging model for order-of-addition experiments in drug combination studies," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    • Handle: RePEc:eee:csdana:v:157:y:2021:i:c:s0167947320302462
    DOI: 10.1016/j.csda.2020.107155
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    1. Shengli Zhao & Zehui Dong & Yuna Zhao, 2022. "Order-of-Addition Orthogonal Arrays with High Strength," Mathematics, MDPI, vol. 10(7), pages 1-17, April.
    2. Zhao, Yuna & Lin, Dennis K.J. & Liu, Min-Qian, 2022. "Optimal designs for order-of-addition experiments," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).

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