|日時||2016年4月15日(金) 14:30–16:00 ※通常と開始時間が異なります|
|場所||電子科学研究所 中央キャンパス総合研究棟2号館 5F北側講義室(北12条西7丁目)|
|所属等||九州大学大学院理学研究院生物科学部門 & JSTさきがけ|
With the introduction of direct-acting antivirals (DAAs), treatment against hepatitis C virus (HCV) has been rapidly improving. To eradicate this worldwide infectious disease, 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-resistant profiles of drug combinations.
Based on experimental anti-HCV profiles in an HCV cell culture system, we quantified the instantaneous inhibitory potential (IIP), which is the logarithm of the reduction in viral replication events, for both single and multiple drug combination treatments.
From the calculated IIP of 15 anti-HCV drugs, we found that interferon-alpha (IFN-α) and a nucleoside polymerase inhibitor, sofosbuvir (SOF), had the largest potential to inhibit viral replication events.
Profiling of 52 double-combination treatments indicated that the combinations based on a protease inhibitor, simeprevir (SMV), achieved high IIP.
Our modeling also predicted the treatment amount of SOF in a SOF plus SMV combination could be reduced to 41% in comparison to the amount of SOF needed when combined with ledipasvir.
By taking into account clinical concentrations, different SMV-based double-DAA combination under clinical development showed the most desirable IIP score.
Furthermore, quantification analysis of triple-DAA IFN-free combinations suggests that triple DAAs greatly enhanced antiviral activity and reduced the emergence of drug resistant virus compared with double-DAA treatments.
Our novel framework presents basic evidence to consider in the strategy to optimize multidrug treatment and also to increase its cost-effectiveness.
|連絡先||北海道大学電子科学研究所 附属社会創造数学研究センター 人間数理研究分野 長山 雅晴 内線: 3357 firstname.lastname@example.org|