Understanding pharmacokinetic - pharmacodynamic determinants of outcome to inform dose optimisation for non-MDR TB re-treatment patients in Vietnam

了解药代动力学 - 药效学结果的决定因素，为越南非耐多药结核病再治疗患者的剂量优化提供信息

• 批准号: MR/N028376/1
• 负责人: Giancarlo Biagini
• 金额: $ 51.73万
• 依托单位: Liverpool School of Tropical Medicine
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FN028376%2F1
• 关键词: Understanding; pharmacokinetic; pharmacodynamic; determinants; outcome

TB remains a major global public health problem burden, with 9.6 million new cases and 1.2 million deaths in 2014. Vietnam is ranked 12th among the 22 highest TB burden countries (TB). 140 new cases were reported per 100,000 population in 2014. National TB Control Programme data indicates that 6 months of first-line month therapy for new TB patients is not successful in 10% of cases (some patients are still unwell at the end, and others relapse after apparent cure). Only 20-30% of unsuccessful treatments can be attributed to major problems with antibiotic resistance, which requires specialist management. The remainder go on to receive a standard "Category 2" treatment regimen, which is internationally approved but has not been carefully studied. Unfortunately, re-treatment patients on this regimen do not always do well; in Vietnam, the Category 2 regimen results in only 60-75% treatment success. The reason why patients may fail two rounds of treatment is not well understood. One reason could be that the levels of drug in the body (a study known as pharmacokinetics) of some patients is too low to kill the infection. This problem could also be worsened by the fact that the drug levels required to kill the bacteria causing TB (known as Mycobacterium tuberculosis) are not the same in every patient i.e. some patients are infected with a strain of the M. tuberculosis bacteria which can survive higher concentrations of drugs than others. In this project we will focus on the retreatment patient group to determine whether clinical outcome can be explained by measuring individual patient drug levels and carefully studying the ability of TB drugs to kill M tuberculosis. The project will use advanced analytical techniques to measure drug level in patient's blood samples and a number of new laboratory techniques to study how well the drugs kill each M. tuberculosis strain. All of this information will then be combined and analysed using mathematical models to; (i) determine whether the laboratory/analytical measurements can explain the low treatment success rates and (ii) determine whether this information can be used in the future to improve treatment by predicting bad outcomes at an early stage and recommending a better drug course. Data obtained from this study will be shared with other researchers working on TB around the world and will contribute to the wider discussion on tackling TB by designing better treatment. Significantly, this project aims to also increase the local capacity for advanced studies of this type by providing training and mentoring to our Vietnamese colleagues in all of the methodological areas described.

结核病仍然是一个重大的全球公共卫生问题负担，2014年有960万新发病例和120万例死亡。越南在22个结核病负担最高的国家中排名第12位。2014年，每10万人报告了140例新病例。国家结核病控制规划的数据表明，10%的新结核病患者接受6个月的一线月治疗没有成功（一些患者最后仍然不舒服，另一些患者在明显治愈后复发）。只有20-30%的不成功治疗可归因于抗生素耐药性的主要问题，这需要专家管理。其余的人继续接受标准的“第2类”治疗方案，这是国际上批准的，但尚未仔细研究。不幸的是，这种方案的再治疗患者并不总是表现良好;在越南，2类方案的治疗成功率仅为60-75%。患者可能两轮治疗失败的原因尚不清楚。一个原因可能是一些患者体内的药物水平（一项称为药代动力学的研究）太低，无法杀死感染。这个问题也可能由于杀死引起TB的细菌（称为结核分枝杆菌）所需的药物水平在每个患者中不相同而恶化，即一些患者感染了M菌株。结核菌比其他细菌能在更高浓度的药物中存活。在本项目中，我们将重点关注复治患者组，以确定是否可以通过测量个体患者的药物水平和仔细研究结核药物杀死结核分枝杆菌的能力来解释临床结果。该项目将使用先进的分析技术来测量病人血液样本中的药物水平，并使用一些新的实验室技术来研究药物杀死每一个M。结核菌株然后将所有这些信息结合起来，并使用数学模型进行分析，以：（i）确定实验室/分析测量是否可以解释治疗成功率低的原因，以及（ii）确定这些信息是否可以在未来通过在早期预测不良结果并推荐更好的药物疗程来改善治疗。从这项研究中获得的数据将与世界各地从事结核病研究的其他研究人员分享，并将有助于通过设计更好的治疗方法来应对结核病的更广泛的讨论。重要的是，该项目还旨在通过在所述的所有方法领域为我们的越南同事提供培训和指导，提高当地进行这类高级研究的能力。

项目成果

A Quantitative Method for the Study of HIV-1 and Mycobacterium tuberculosis Coinfection.

• DOI: 10.1093/infdis/jiac491
• 发表时间: 2023-03-01
• 期刊: The Journal of infectious diseases

Antimicrobial Therapies - Methods and Protocols

抗菌疗法 - 方法和方案

• DOI: 10.1007/978-1-0716-1358-0_23
• 发表时间: 2021
• 作者: Donnellan S

Intracellular PD Modelling (PDi) for the Prediction of Clinical Activity of Increased Rifampicin Dosing.

用于预测增加利福平剂量的临床活性的细胞内 PD 模型 (PDi)。

• DOI: 10.3390/pharmaceutics11060278
• 发表时间: 2019
• 期刊: Pharmaceutics
• 影响因子: 5.4
• 作者: Aljayyoussi G

Pharmacokinetic-Pharmacodynamic modelling of intracellular Mycobacterium tuberculosis growth and kill rates is predictive of clinical treatment duration.

• DOI: 10.1038/s41598-017-00529-6
• 发表时间: 2017-03-29
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Aljayyoussi G;Jenkins VA;Sharma R;Ardrey A;Donnellan S;Ward SA;Biagini GA
• 通讯作者: Biagini GA