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

Yusuke Kakizoe, Yoshiki Koizumi, Yukino Ikoma, Hirofumi Ohashi, Takaji Wakita, Shingo Iwami, Koichi Watashi

研究成果: ジャーナルへの寄稿学術誌査読

1 被引用数 (Scopus)

抄録

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.

本文言語英語
論文番号4
ジャーナルTheoretical Biology and Medical Modelling
18
1
DOI
出版ステータス出版済み - 12月 2021
外部発表はい

!!!All Science Journal Classification (ASJC) codes

  • モデリングとシミュレーション
  • 健康情報学

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