标题： 设计减轻不依从性的药物方案 显示英文标题

标题： Designing drug regimens that mitigate nonadherence

摘要： 药物依从性是慢性疾病药物治疗中的一个众所周知的问题。 了解不依从性如何影响治疗效果，由于临床试验的伦理问题，即强制患者跳过正在测试的药物剂量，实际患者错过剂量的时间不可预测，以及许多可能减轻或加剧不依从性有害影响的竞争变量（如药代动力学吸收和消除速率、给药间隔、剂量大小、依从率等），使得这一问题变得困难。 在本文中，我们制定了一个不完全依从患者药物浓度的数学模型。 我们的模型采用标准的一室药代动力学模型，具有第一阶吸收和消除，只是患者只在规定给药时间的一个比例时服药。 剂量是随机错过的，我们使用随机分析来研究体内产生的随机药物水平。 然后，我们利用数学结果提出设计对不依从性具有鲁棒性的药物方案的原则。 特别是，我们量化了缓释药物对不依从性的抵抗力，这在某些情况下相当显著，并且我们展示了在药物吸收或消除速率相对于给药间隔较慢的情况下，在错过剂量后服用双倍剂量的好处。 我们进一步利用结果比较了一些抗癫痫和抗精神病药物方案。 显示英文摘要

摘要： Medication adherence is a well-known problem for pharmaceutical treatment of chronic diseases. Understanding how nonadherence affects treatment efficacy is made difficult by the ethics of clinical trials that force patients to skip doses of the medication being tested, the unpredictable timing of missed doses by actual patients, and the many competing variables that can either mitigate or magnify the deleterious effects of nonadherence, such as pharmacokinetic absorption and elimination rates, dosing intervals, dose sizes, adherence rates, etc. In this paper, we formulate and analyze a mathematical model of the drug concentration in an imperfectly adherent patient. Our model takes the form of the standard single compartment pharmacokinetic model with first order absorption and elimination, except that the patient takes medication only at a given proportion of the prescribed dosing times. Doses are missed randomly, and we use stochastic analysis to study the resulting random drug level in the body. We then use our mathematical results to propose principles for designing drug regimens that are robust to nonadherence. In particular, we quantify the resilience of extended release drugs to nonadherence, which is quite significant in some circumstances, and we show the benefit of taking a double dose following a missed dose if the drug absorption or elimination rate is slow compared to the dosing interval. We further use our results to compare some antiepileptic and antipsychotic drug regimens.