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Optimum Experimental Design for Patient Specific Mathematical Leukopenia Models

机译：针对特定患者的数学白细胞减少症模型的最佳实验设计

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Abstract: Mathematical models are essential for simulation-driven decision support for clinical doctors. For an estimation of parameters for patient specific models, values such as the number of certain blood cells need to be measured. In this paper we focus on leukopenia, a clinically important side effect arising from the treatment of leukemia with chemotherapy. A mathematical leukopenia model is presented describing the dynamics of leukocytes and we show that the standard deviations of the parameter estimates depend strongly on the timing of the measurements. We discuss the issue of measurement time points for two patients being in the consolidation phase of acute myeloid leukemia and provide optimal solutions. Optimized measurement time points and the thus enabled accurate simulations have a large impact: drug treatments can be adapted individually and patients may safely leave the hospital for longer and more convenient time intervals. The dynamics of leukocytes are modeled by a system of ordinary differential equations and the chemotherapy with cytarabine is described by a pharmacokinetics/pharmacodynamics model consisting of two compartments and a log-linear function representing the drug effect. The measurement time points are optimized by optimal experimental design. With optimal experimental design an average parameter uncertainty reduction of 57% ( Patient 1 ) and 80% ( Patient 2 ) can be achieved compared to the clinical experimental designs, with the same total number of measurements. These encouraging results motivate further research and an extension of the data basis to more patients.
机译：摘要：数学模型对于临床医生基于仿真的决策支持至关重要。为了估计患者特定模型的参数，需要测量诸如某些血细胞数量的值。在本文中，我们着重于白细胞减少症，这是化学疗法治疗白血病所产生的临床上重要的副作用。提出了描述白细胞动力学的数学白细胞减少症模型，并且我们表明参数估计值的标准偏差在很大程度上取决于测量的时间。我们讨论了急性髓性白血病巩固期的两名患者的测量时间点问题，并提供了最佳解决方案。优化的测量时间点以及由此实现的精确模拟具有很大的影响：可以单独调整药物治疗，患者可以安全地出院更长，更方便的时间间隔。用常微分方程组对白细胞的动力学建模，用由两个区室和代表药物作用的对数线性函数组成的药代动力学/药效学模型描述阿糖胞苷的化疗。通过最佳实验设计优化了测量时间点。与最佳的实验设计相比，在相同的测量总数下，与临床实验设计相比，平均参数不确定性降低了57％（患者1）和80％（患者2）。这些令人鼓舞的结果激励了进一步的研究，并将数据基础扩展到更多的患者。

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