Efficacy of SPR720 in murine models of non-tuberculous mycobacterial pulmonary infection.

The Journal of antimicrobial chemotherapy(2024)

引用 0|浏览2
暂无评分
摘要
BACKGROUND:Non-tuberculous mycobacterial pulmonary disease (NTM-PD) is increasing worldwide, with Mycobacterium avium complex (MAC) and Mycobacterium abscessus as the predominant pathogens. Current treatments are poorly tolerated and modestly effective, highlighting the need for new treatments. SPR719, the active moiety of the benzimidazole prodrug SPR720, inhibits the ATPase subunits of DNA gyrase B, a target not exploited by current antibiotics, and therefore, no cross-resistance is expected with standard-of-care (SOC) agents. OBJECTIVES:To evaluate the in vitro activity of SPR719 against MAC and M. abscessus clinical isolates, including those resistant to SOC agents, and in vivo efficacy of SPR720 in murine non-tuberculous mycobacteria (NTM) pulmonary infection models. METHODS:NTM isolates were tested for susceptibility to SPR719. Chronic C3HeB/FeJ and severe combined immunodeficient murine models of pulmonary infection were used to assess efficacy of SPR720 against MAC and M. abscessus, respectively. RESULTS:SPR719 was active against MAC (MIC90, 2 mg/L) and M. abscessus (MIC90, 4 mg/L) clinical isolates. Efficacy of SPR720 was demonstrated against MAC pulmonary infection, both as a monotherapy and in combination with SOC agents. SPR720 monotherapy exhibited dose-dependent reduction in bacterial burden, with the largest reduction observed when combined with clarithromycin and ethambutol. Efficacy of SPR720 was also demonstrated against M. abscessus pulmonary infection where monotherapy exhibited a dose-dependent reduction in bacterial burden with further reductions detected when combined with SOC agents. CONCLUSIONS:In vitro activity of SPR720 against common NTM pathogens and efficacy in murine infections warrant the continued clinical evaluation of SPR720 as a new oral option for the treatment of NTM-PD.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要