Radius additivity score: a novel combination index for tumour growth inhibition in fixed-dose xenograft studies

Frontiers in Pharmacology

Pharmacology

Heinrich J. Huber¹  Lu Tan¹  Jake Dickinson²  Nicola Melillo²  Hitesh B. Mistry³ 

[1] Division Drug Discovery Sciences, Boehringer Ingelheim RCV GmbH & Co KG, Vienna, Austria;Seda Pharmaceutical Developments Services Unit D Cheadle Royal Business Park, Stockport, United Kingdom;Seda Pharmaceutical Developments Services Unit D Cheadle Royal Business Park, Stockport, United Kingdom;Division of Pharmacy, University of Manchester, Manchester, United Kingdom;

关键词: drug combination;    biostatistic;    mathematical model;    synergy;    xenograft;   

DOI  :  10.3389/fphar.2023.1272058

 received in 2023-08-03, accepted in 2023-09-29,  发布年份 2023

来源: Frontiers

【 摘 要 】

The effect of combination therapies in many cancers has often been shown to be superior to that of monotherapies. This success is commonly attributed to drug synergies. Combinations of two (or more) drugs in xenograft tumor growth inhibition (TGI) studies are typically designed at fixed doses for each compound. The available methods for assessing synergy in such study designs are based on combination indices (CI) and model-based analyses. The former methods are suitable for screening exercises but are difficult to verify in in vivo studies, while the latter incorporate drug synergy in semi-mechanistic frameworks describing disease progression and drug action but are unsuitable for screening. In the current study, we proposed the empirical radius additivity (Rad-add) score, a novel CI for synergy detection in fixed-dose xenograft TGI combination studies. The Rad-add score approximates model-based analysis performed using the semi-mechanistic constant-radius growth TGI model. The Rad-add score was compared with response additivity, defined as the addition of the two response values, and the bliss independence model in combination studies derived from the Novartis PDX dataset. The results showed that the bliss independence and response additivity models predicted synergistic interactions with high and low probabilities, respectively. The Rad-add score predicted synergistic probabilities that appeared to be between those predicted with response additivity and the Bliss model. We believe that the Rad-add score is particularly suitable for assessing synergy in the context of xenograft combination TGI studies, as it combines the advantages of CI approaches suitable for screening exercises with those of semi-mechanistic TGI models based on a mechanistic understanding of tumor growth.

【 授权许可】

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Copyright © 2023 Melillo, Dickinson, Tan, Mistry and Huber.