联合疗法在许多癌症中的效果常常被证明优于单一疗法。这种成功通常归因于药物的协同作用。在异种移植肿瘤生长抑制（TGI）研究中，两种（或多种）药物的组合通常被设计为每种化合物的固定剂量。评估此类研究设计中的协同作用的可用方法基于组合指数 (CI) 和基于模型的分析。前一种方法适合筛选练习，但难以在体内研究中验证，而后者将药物协同作用纳入描述疾病进展和药物作用的半机械框架中，但不适合筛选。在当前的研究中，我们提出了经验半径加和性（Rad-add）评分，这是一种用于固定剂量异种移植 TGI 组合研究中协同检测的新型 CI。 Rad-add 分数近似于使用半机械恒定半径生长 TGI 模型执行的基于模型的分析。将 Rad-add 评分与响应相加性（定义为两个响应值相加）以及源自诺华 PDX 数据集的组合研究中的幸福独立模型进行比较。结果表明，幸福独立性和响应可加性模型分别预测了高概率和低概率的协同相互作用。 Rad-add 分数预测的协同概率似乎介于响应可加性预测值和 Bliss 模型预测值之间。我们认为，Rad-add 评分特别适合评估异种移植组合 TGI 研究中的协同作用，因为它结合了适合筛选练习的 CI 方法的优点与基于对肿瘤机制的理解的半机械 TGI 模型的优点增长。版权所有 © 2023 Melillo、Dickinson、Tan、Mistry 和 Huber。

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