抗生素相互作用对抗生素耐药性演变的数学建模:一种分析方法
Ramin Nashebi1, Murat Sari2, Seyfullah Enes Kotil3,4
1Department of Mathematics, Yildiz Technical University, Istanbul, Turkey.
PeerJ
|March 1, 2024
概括
抗生素组合是对抗耐药病原体的关键. 对野生型细菌的敌对相互作用显著减缓了耐药性的发展,比对突变的相互作用更为如此.
科学领域:
- 微生物学 微生物学
- 进化生物学 进化生物学
- 药理学 药理学是指药理学的学科.
背景情况:
- 抗生素耐药性是一个日益增长的全球健康威胁,需要新的治疗策略,如抗生素组合.
- 抗生素之间的相互作用 (协同作用或对抗作用) 可以显著改变治疗结果,并影响细菌耐药性的演变.
- 这些相互作用对抗性发展的影响在野生型和突变 (耐药) 细菌菌株之间可能有所不同.
研究的目的:
- 研究抗生素相互作用 (协同作用和对抗作用) 对野生型与突变细菌群体抗菌耐药性演变的差异影响.
- 确定对抗野生型细菌的有益作用是否超过其在减缓耐药性获取方面对突变体的潜在有害作用.
主要方法:
- 开发和分析一个数学模型,模拟各种抗生素组合疗法下的野生型和突变细菌的种群动态.
- 均衡的稳定性分析有助于理解无细菌,全变异和共存状态.
- 数字模拟可用于可视化时间动态和验证分析结果.
主要成果:
- 抗生素对野生型细菌的相互作用对降低耐药性发展率的影响比对突变菌的相互作用更大.
- 针对野生型细菌的敌对抗生素相互作用对于减缓耐药突变的出现和扩散至关重要.
- 对抗已经具有抗性突变的敌对相互作用对抗性进化产生最小的影响,并可能加速它.
结论:
- 选择抗生素相互作用,特别是对野生型细菌的对抗性,对于有效减缓抗菌素耐药性的获得至关重要.
- 专注于向野生型细菌的抗生素相互作用,为打击抗生素耐药性提供了比向耐药突变物更有前途的策略.
相关概念视频
Antibiotic Selection
53.5K
Overview
53.5K
Pharmacokinetic Models: Overview
682
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
682
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
127
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
127
Mechanistic Models: Compartment Models in Individual and Population Analysis
40
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
40
Combined Effects of Drugs: Synergism
3.9K
Synergism is a useful mechanism where combining two or more drugs is more effective than each constituent used alone. Such combinations are also called supra-additive interactions. The drugs collectively enhance the final therapeutic effect by acting on different targets. Another advantage is that the low dose of each constituent drug is sufficient to achieve the desired effect. This helps reduce the duration of therapy and lower the adverse effects of these drugs.
Such synergistic combinations...
Such synergistic combinations...
3.9K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
69
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
69


