Faculté de Pharmacie, Université de Montréal, C.P. 6128, Succ. Centre-ville, Montréal, QC H3C3J7, Canada.
J Pharmacokinet Pharmacodyn. 2009 Jun;36(3):221-38. doi: 10.1007/s10928-009-9119-7. Epub 2009 Jun 25.
Fine individual drug intake data, generally collected by electronic monitoring devices, reveal that individual marked random patterns are likely to persist through long therapeutic periods. This work aims to establish the relationship between irregularity in drug intake and its potential impact on therapeutic outcomes, which will also serve as a basis for more objective interventions. First we proposed a direct way to extract the necessary information representing the patient drug intake history. To provide a fair evaluation of the pharmacological performance, we revisited several classical pharmacological indices and proposed new ones in the stochastic context of patient's drug intake irregularity. To illustrate our procedure, we have considered two cases of HIV treatment using a combination of lopinavir/ritonavir (Kaletra@) for once daily and twice daily regimens. We have quantified the impact on therapeutic effect of various characteristics in dosing histories, namely missing doses and deviations from nominal times. Using our newly defined pharmacological indices, we clearly showed the ability of our probabilistic approach in measuring the impact of noncompliance. As a direct fallout, we have discussed strategies to attenuate the impact of noncompliance through an optimal design of dosing regimen.
详细的个体药物摄入数据，通常通过电子监测设备收集，揭示了个体明显的随机模式可能会持续很长的治疗期。这项工作旨在建立药物摄入不规律与其对治疗结果的潜在影响之间的关系，这也将为更客观的干预提供依据。首先，我们提出了一种直接提取代表患者药物摄入史的必要信息的方法。为了公平评估药物的疗效，我们在患者药物摄入不规律的随机背景下重新审视了几个经典的药理学指标，并提出了新的指标。为了说明我们的过程，我们考虑了两种 HIV 治疗情况，使用洛匹那韦/利托那韦（克力芝）每天一次和每天两次的方案。我们量化了给药史中各种特征（即漏服和偏离标称时间）对治疗效果的影响。使用我们新定义的药理学指标，我们清楚地表明了我们的概率方法在衡量不依从性影响方面的能力。作为直接的结果，我们讨论了通过优化给药方案设计来减轻不依从性影响的策略。
