Quantifying antiviral activity optimizes drug combinations against hepatitis C virus infection

Yoshiki Koizumi, Hirofumi Ohashi, Syo Nakajima, Yasuhito Tanaka, Takaji Wakita, Alan S. Perelson, Shingo Iwami, Koichi Watashi

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

With the introduction of direct-acting antivirals (DAAs), treatment against hepatitis C virus (HCV) has significantly improved. To manage and control this worldwide infectious disease better, the "best" multidrug treatment is demanded based on scientific evidence. However, there is no method available that systematically quantifies and compares the antiviral efficacy and drug-resistance profiles of drug combinations. Based on experimental anti-HCV profiles in a cell culture system, we quantified the instantaneous inhibitory potential (IIP), which is the logarithm of the reduction in viral replication events, for both single drugs and multiple-drug combinations. From the calculated IIP of 15 anti-HCV drugs from different classes [telaprevir, danoprevir, asunaprevir, simeprevir, sofosbuvir (SOF), VX-222, dasabuvir, nesbuvir, tegobuvir, daclatasvir, ledipasvir, IFN-α, IFN-λ1, cyclosporin A, and SCY-635], we found that the nucleoside polymerase inhibitor SOF had one of the largest potentials to inhibit viral replication events. We also compared intrinsic antiviral activities of a panel of drug combinations. Our quantification analysis clearly indicated an advantage of triple-DAA treatments over double-DAA treatments, with triple-DAA treatments showing enhanced antiviral activity and a significantly lower probability for drug resistance to emerge at clinically relevant drug concentrations. Our framework provides quantitative information to consider in designing multidrug strategies before costly clinical trials.

Original languageEnglish
Pages (from-to)1922-1927
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume114
Issue number8
DOIs
Publication statusPublished - Feb 21 2017

All Science Journal Classification (ASJC) codes

  • General

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