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首页> 外文会议>2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference >A mathematical framework for analyzing drug combination toxicity for personalized medicine applications
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A mathematical framework for analyzing drug combination toxicity for personalized medicine applications

机译：用于个性化药物应用的药物组合毒性分析的数学框架

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摘要

The use of drug combinations to increase efficacy and lower resistance to therapy for personalized cancer medicine is being commonly recognized. Approaches have been recently designed to address the selection of drug combinations that can be highly effective across tumor cells but limited research have been conducted on the toxicity of these unique drug combinations. In this article, we approach this problem of combination drug toxicity by analyzing drug synergy over in vitro normal cell lines and generate combination drug concentrations whose combined effect on normal cell lines is less than the maximum monotherapy effect at approved concentrations. We present a mathematical framework for combination response estimation among multiple cell cultures along with stochastic analysis of prediction uncertainty. Results indicate the ability of the proposed framework to generate feasibly combination drug concentrations satisfying monotherapy toxicity constraints.
机译：人们普遍认识到使用药物组合来提高疗效和降低对个性化癌症药物的治疗抵抗力。最近已经设计出方法来解决在肿瘤细胞间可能非常有效的药物组合的选择，但是对这些独特药物组合的毒性进行的研究有限。在本文中，我们通过分析体外正常细胞系上的药物协同作用并产生其对正常细胞系的联合作用小于批准浓度下的最大单一疗法作用的联合药物浓度来解决组合药物毒性的问题。我们提出了一种数学框架，用于在多个细胞文化之间进行组合响应估计以及对预测不确定性的随机分析。结果表明，所提出的框架能够产生满足单一疗法毒性约束的可行组合药物浓度的能力。

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