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A therapeutic drug monitoring algorithm for refining the imatinib trough level obtained at different sampling times.

机译:一种治疗药物监测算法,用于改进在不同采样时间获得的伊马替尼谷水平。

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BACKGROUND: Correlation analyses have demonstrated that maintaining an adequate imatinib (IM) trough concentration would be important for clinical response in patients with chronic myeloid leukemia (CML) and Kit-positive gastrointestinal stromal tumors. The objectives of the current work were to use a pharmacokinetic model to refine the trough levels obtained at different sampling times and to propose a therapeutic drug monitoring algorithm and an acceptable sampling time window for imatinib trough sampling. METHODS: The pharmacokinetics of IM in patients (pts) with CML were characterized based on historical data from a Phase III study. In the elimination phase the concentration of IM (C(t)) follows a mono-exponential decline, and the standardized trough concentration (C(min,std) = C(tau)) can be described by a simple algorithm C(min,std) = C(t)* exp(k(e) x Delta t), where Delta t = t - tau, and tau is 24 hours for qd or 12 hours for bid dosing and k(e) is the elimination rate constant. The percent deviation of C(t) from C(min,std) was simulated for different Delta t and k(e) values to define a sampling time window Delta t, within which the percent deviation is <20%. RESULTS: Simulation analysis shows that C(t) is largely dependent on Delta t and k(e). The percent deviation of C(t) at 3 hours before or after tau from C(min,std) will be 7.1%, 13.1%, and 23.4% for pts with low, typical, and high k(e) values, 0.023/hour, 0.041/hour, and 0.070/hour, respectively. However, if a correction is made for C(t) by the algorithm using the typical k(e) value of 0.041 per hour, the percent deviation at 3 hours will be reduced to 5.3%, 0%, and 9.1% for pts with low, typical, and high k(e) values, respectively. Even if the sampling window is extended to +/-6 hours, the corresponding percent deviation will still be reasonable: 10.2%, 0%, and 19.0%, respectively. CONCLUSION: By using the algorithm, the pharmacokinetic sampling window can be extended to a wider window to make the trough sampling easy to implement in the clinical setting, provided that the sampling time and dosing time are accurately recorded.
机译:背景:相关性分析表明,维持适当的伊马替尼(IM)谷浓度对于慢性粒细胞白血病(CML)和Kit阳性胃肠道间质瘤患者的临床反应至关重要。当前工作的目的是使用药代动力学模型完善在不同采样时间获得的谷水平,并提出治疗药物监测算法和伊马替尼谷采样的可接受采样时间窗口。方法:基于III期研究的历史数据,对IM在CML患者(pts)中的药代动力学进行了表征。在消除阶段,IM的浓度(C(t))随单指数下降,标准化的谷浓度(C(min,std)= C(tau))可以通过简单的算法C(min, std)= C(t)* exp(k(e)x Delta t),其中Delta t = t-tau,qd的tau是24小时,而投标计量的tau是12小时,而k(e)是消除率常数。针对不同的Delta t和k(e)值模拟了C(t)与C(min,std)的百分比偏差,以定义采样时间窗口Delta t,其中百分比偏差<20%。结果:仿真分析表明C(t)在很大程度上取决于Delta t和k(e)。 k(e)值低,典型和高的pts在tau之前或之后3小时与C(min,std)的C(t)的百分比偏差分别为7.1%,13.1%和23.4%小时,0.041 /小时和0.070 /小时。但是,如果通过算法使用每小时0.041的典型k(e)值对C(t)进行校正,则对于具有以下条件的pts,3小时的百分比偏差将减少到5.3%,0%和9.1% k(e)值分别为低,典型和高。即使将采样窗口延长到+/- 6小时,相应的百分比偏差仍将是合理的:分别为10.2%,0%和19.0%。结论:通过使用该算法,只要准确记录采样时间和给药时间,就可以将药代动力学采样窗口扩展到更宽的窗口,从而使波谷采样在临床环境中易于实施。

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