Cicchese Joseph M, Dartois Véronique, Kirschner Denise E, Linderman Jennifer J
Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, United States.
Public Health Research Institute, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, NJ, United States.
Front Pharmacol. 2020 Mar 24;11:333. doi: 10.3389/fphar.2020.00333. eCollection 2020.
Tuberculosis (TB) remains as one of the world's deadliest infectious diseases despite the use of standardized antibiotic therapies. Recommended therapy for drug-susceptible TB is up to 6 months of antibiotics. Factors that contribute to lengthy regimens include antibiotic underexposure in lesions due to poor pharmacokinetics (PK) and complex granuloma compositions, but it is difficult to quantify how individual antibiotics are affected by these factors and to what extent these impact treatments. We use our next-generation multi-scale computational model to simulate granuloma formation and function together with antibiotic pharmacokinetics and pharmacodynamics, allowing us to predict conditions leading to granuloma sterilization. In this work, we focus on how PK variability, determined from human PK data, and granuloma heterogeneity each quantitatively impact granuloma sterilization. We focus on treatment with the standard regimen for TB of four first-line antibiotics: isoniazid, rifampin, ethambutol, and pyrazinamide. We find that low levels of antibiotic concentration due to naturally occurring PK variability and complex granulomas leads to longer granuloma sterilization times. Additionally, the ability of antibiotics to distribute in granulomas and kill different subpopulations of bacteria contributes to their specialization in the more efficacious combination therapy. These results can inform strategies to improve antibiotic therapy for TB.
尽管使用了标准化的抗生素疗法，但结核病（TB）仍然是世界上最致命的传染病之一。针对药物敏感型结核病的推荐疗法是使用长达6个月的抗生素。导致治疗方案冗长的因素包括：由于药代动力学（PK）不佳以及肉芽肿成分复杂，病变部位的抗生素暴露不足，但很难量化这些因素如何影响每种抗生素以及对治疗产生多大影响。我们使用下一代多尺度计算模型来模拟肉芽肿的形成和功能以及抗生素的药代动力学和药效学，从而使我们能够预测导致肉芽肿灭菌的条件。在这项工作中，我们重点研究由人类PK数据确定的PK变异性和肉芽肿异质性如何分别定量影响肉芽肿灭菌。我们重点关注使用四种一线抗生素（异烟肼、利福平、乙胺丁醇和吡嗪酰胺）的结核病标准疗法进行治疗。我们发现，由于自然存在的PK变异性和复杂的肉芽肿导致抗生素浓度较低，会使肉芽肿灭菌时间延长。此外，抗生素在肉芽肿中分布并杀死不同细菌亚群的能力有助于它们在更有效的联合治疗中发挥特殊作用。这些结果可为改善结核病抗生素治疗的策略提供参考。
