所需浓度指数量化抗丙型肝炎病毒感染的有效药物组合。

Q1 Mathematics
Yusuke Kakizoe, Yoshiki Koizumi, Yukino Ikoma, Hirofumi Ohashi, Takaji Wakita, Shingo Iwami, Koichi Watashi
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引用次数: 1

摘要

成功的临床药物开发需要基于临床前数据合理设计联合治疗方案。抗丙型肝炎病毒(HCV)药物在抗病毒作用上表现出显著的多样性。剂量反应评估可用于确定综合治疗期间不同抗病毒效果的参数。在目前的研究中,采用实验和数学相结合的方法来比较和评分不同的抗hcv治疗组合。生成了一个“所需浓度指数”,并用于对可能的双药和三联药联合治疗1b和2a型HCV的抗病毒特性进行排序。排名因目标HCV基因型而异。有趣的是,多药(双药和三联药)治疗不仅增强了抗病毒活性,而且降低了基因型特异性疗效,这表明多药治疗的另一个优势。目前的研究提供了一种定量方法来分析针对病毒基因型的药物组合,从而更好地为临床药物开发提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Required concentration index quantifies effective drug combinations against hepatitis C virus infection.

Required concentration index quantifies effective drug combinations against hepatitis C virus infection.

Required concentration index quantifies effective drug combinations against hepatitis C virus infection.

Required concentration index quantifies effective drug combinations against hepatitis C virus infection.

Successful clinical drug development requires rational design of combination treatments based on preclinical data. Anti-hepatitis C virus (HCV) drugs exhibit significant diversity in antiviral effect. Dose-response assessments can be used to determine parameters profiling the diverse antiviral effect during combination treatment. In the current study, a combined experimental and mathematical approaches were used to compare and score different combinations of anti-HCV treatments. A "required concentration index" was generated and used to rank the antiviral profile of possible double- and triple-drug combinations against HCV genotype 1b and 2a. Rankings varied based on target HCV genotype. Interestingly, multidrug (double and triple) treatment not only augmented antiviral activity, but also reduced genotype-specific efficacy, suggesting another advantage of multidrug treatment. The current study provides a quantitative method for profiling drug combinations against viral genotypes, to better inform clinical drug development.

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来源期刊
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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