کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6370149 1318830 2015 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A computational tool integrating host immunity with antibiotic dynamics to study tuberculosis treatment
ترجمه فارسی عنوان
یک ابزار محاسباتی که ایمنی میزبان را با استفاده از پویایی آنتی بیوتیک برای بررسی بیماری سل بررسی می کند
کلمات کلیدی
فارماکودینامیک، فارماکوکینتیک، مدل مبتنی بر عامل، گرانولومای، شیب آنتی بیوتیک،
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
چکیده انگلیسی


- First computational TB granuloma model with spatial aspects of immunity and antibiotics.
- Hybrid agent-based model and ordinary differential equation models.
- Suboptimal antibiotic exposure may contribute to long treatment and treatment failure.
- Target bacterial populations are mainly intracellular during treatment.
- Pre-treatment infection severity is predictive of treatment outcome.

While active tuberculosis (TB) is a treatable disease, many complex factors prevent its global elimination. Part of the difficulty in developing optimal therapies is the large design space of antibiotic doses, regimens and combinations. Computational models that capture the spatial and temporal dynamics of antibiotics at the site of infection can aid in reducing the design space of costly and time-consuming animal pre-clinical and human clinical trials. The site of infection in TB is the granuloma, a collection of immune cells and bacteria that form in the lung, and new data suggest that penetration of drugs throughout granulomas is problematic. Here we integrate our computational model of granuloma formation and function with models for plasma pharmacokinetics, lung tissue pharmacokinetics and pharmacodynamics for two first line anti-TB antibiotics. The integrated model is calibrated to animal data. We make four predictions. First, antibiotics are frequently below effective concentrations inside granulomas, leading to bacterial growth between doses and contributing to the long treatment periods required for TB. Second, antibiotic concentration gradients form within granulomas, with lower concentrations toward their centers. Third, during antibiotic treatment, bacterial subpopulations are similar for INH and RIF treatment: mostly intracellular with extracellular bacteria located in areas non-permissive for replication (hypoxic areas), presenting a slowly increasing target population over time. Finally, we find that on an individual granuloma basis, pre-treatment infection severity (including bacterial burden, host cell activation and host cell death) is predictive of treatment outcome.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Theoretical Biology - Volume 367, 21 February 2015, Pages 166-179
نویسندگان
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