Gumbo Tawanda, Louie Arnold, Liu Weiguo, Brown David, Ambrose Paul G, Bhavnani Sujata M, Drusano George L
Division of Infectious Diseases, UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX 75390-9113, USA.
Antimicrob Agents Chemother. 2007 Jul;51(7):2329-36. doi: 10.1128/AAC.00185-07. Epub 2007 Apr 16.
Isoniazid, administered as part of combination antituberculosis therapy, is responsible for most of the early bactericidal activity (EBA) of the regimen. However, the emergence of Mycobacterium tuberculosis resistance to isoniazid is a major problem. We examined the relationship between isoniazid exposure and M. tuberculosis microbial kill, as well as the emergence of resistance, in our in vitro pharmacodynamic model of tuberculosis. Since single-nucleotide polymorphisms of the N-acetyltransferase-2 gene lead to two different clearances of isoniazid from serum in patients, we simulated the isoniazid concentration-time profiles encountered in both slow and fast acetylators. Both microbial kill and the emergence of resistance during monotherapy were associated with the ratio of the area under the isoniazid concentration-time curve from 0 to 24 h (AUC(0-24)) to the isoniazid MIC. The time in mutant selection window hypothesis was rejected. Next, we utilized the in vitro relationship between the isoniazid AUC(0-24)/MIC ratio and microbial kill, the distributions of isoniazid clearance in populations with different percentages of slow and fast acetylators, and the distribution of isoniazid MICs for isonazid-susceptible M. tuberculosis clinical isolates in Monte Carlo simulations to calculate the EBA expected for approximately 10,000 patients treated with 300 mg of isoniazid. For those patient populations in which the proportion of fast acetylators and the isoniazid MICs were high, the average EBA of the standard dose was approximately 0.3 log(10) CFU/ml/day and was thus suboptimal. Our approach, which utilizes preclinical pharmacodynamics and the genetically determined multimodal distributions of serum clearances, is a preclinical tool that may be able to predict the EBAs of various doses of new antituberculosis drugs.
异烟肼作为联合抗结核治疗的一部分给药,是该治疗方案早期杀菌活性(EBA)的主要贡献者。然而,结核分枝杆菌对异烟肼产生耐药性是一个主要问题。我们在结核病体外药效学模型中研究了异烟肼暴露与结核分枝杆菌杀灭以及耐药性出现之间的关系。由于N - 乙酰转移酶 - 2基因的单核苷酸多态性导致患者血清中异烟肼的清除率存在两种不同情况,我们模拟了慢乙酰化者和快乙酰化者体内异烟肼的浓度 - 时间曲线。单药治疗期间的细菌杀灭和耐药性出现均与0至24小时异烟肼浓度 - 时间曲线下面积(AUC(0 - 24))与异烟肼最低抑菌浓度(MIC)的比值相关。突变选择窗假说被否定。接下来,我们利用异烟肼AUC(0 - 24)/MIC比值与细菌杀灭之间的体外关系、不同百分比的慢乙酰化者和快乙酰化者群体中异烟肼清除率的分布,以及蒙特卡洛模拟中对异烟肼敏感的结核分枝杆菌临床分离株的异烟肼MIC分布,来计算约10,000例接受300毫克异烟肼治疗患者的预期EBA。对于快乙酰化者比例和异烟肼MIC较高的患者群体,标准剂量的平均EBA约为0.3 log(10) CFU/ml/天,因此并不理想。我们的方法利用临床前药效学和血清清除率的基因决定多模态分布,是一种临床前工具,或许能够预测各种剂量新型抗结核药物的EBA。