Fermín Lisandro J, Lévy-Véhel Jacques
CIMFAV, Instituto de Ingeniería Matemática, Facultad de Ingeniería, Universidad de Valparaíso, Valparaíso, Chile.
Institut National de Recherche en Informatique et en Automatique (INRIA) Le Chesnay, Le Chesnay, France.
J Appl Stat. 2020 Jan 7;47(13-15):2525-2545. doi: 10.1080/02664763.2019.1711030. eCollection 2020.
We propose a Piecewise-Deterministic Markov Process (PDMP) to model the drug concentration in the case of multiple intravenous-bolus (multi-IV) doses and poor patient adherence situation: the scheduled time and doses of drug administration are not respected by the patient, the drug administration considers switching regime with random drug intake times. We study the randomness of drug concentration and derive probability results on the stochastic dynamics using the PDMP theory, focusing on two aspects of practical relevance: the variability of the concentration and the regularity of its stationary probability distribution. The main result show as the regularity of the concentration is governed by a parameter, which quantifies in a precise way the situations where drug intake times are too scarce concerning the elimination rate. Our approach is novel for the study of the regularity of the stationary distribution in PDMP models. This article extends the results given in [J. Lévy-Véhel and P.E. Lévy-Véhel, Variability and singularity arising from poor compliance in a pharmacodynamical model I: The multi-IV case, J. Pharmacokinet. Pharmacodyn. 40 (2013), pp. 15-39], by considering more realistic irregular dosing schedules. The computations permit precise assessment of the effect of various significant parameters such as the mean rate of intake, the elimination rate, and the mean dose. They quantify how much poor adherence will affect the regimen. Our results help to understand the consequences of poor adherence.
我们提出一种分段确定性马尔可夫过程(PDMP),用于模拟多次静脉推注(multi-IV)给药且患者依从性差的情况下的药物浓度:患者未遵循预定的给药时间和剂量,给药考虑采用随机服药时间的转换方案。我们研究药物浓度的随机性,并利用PDMP理论推导随机动力学的概率结果,重点关注两个具有实际相关性的方面:浓度的变异性及其平稳概率分布的规律性。主要结果表明,浓度的规律性由一个参数控制,该参数以精确的方式量化了服药时间相对于消除率过于稀少的情况。我们的方法对于研究PDMP模型中平稳分布的规律性是新颖的。本文扩展了[J. Lévy-Véhel和P.E. Lévy-Véhel,药代动力学模型中依从性差引起的变异性和奇异性I:多IV情况,《药代动力学与药物代谢杂志》40(2013),第15 - 39页]中给出的结果,通过考虑更现实的不规则给药方案。这些计算允许精确评估各种重要参数的影响,如平均摄入率、消除率和平均剂量。它们量化了依从性差将对治疗方案产生多大影响。我们的结果有助于理解依从性差的后果。