Successful projection of the time course of drug concentration in plasma during a 1-year period from electronically compiled dosing-time data used as input to individually parameterized pharmacokinetic models
Successful projection of the time course of drug concentration in plasma during a 1-year period from electronically compiled dosing-time data used as input to individually parameterized pharmacokinetic models
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DOI：
10.1177/0091270004274433
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发表时间：
2005-04-01
影响因子：
2.9
通讯作者：
Urquhart, J
中科院分区：
文献类型：
--
作者：
Vrijens, B;Tousset, E;Urquhart, J
药代动力学研究依赖于在相对于预定给药间隔的时间采集血样。密集采样通常是在直接观察剂量服用的情况下进行的，虽然成本很高，但实际上消除了实际给药时间的不确定性。相比之下，在群体药代动力学研究中进行的稀疏采样依赖于患者报告的给药时间，作者试图通过将电子监测添加到通常的患者报告的关闭时间来评估其准确性。该研究涉及35例未接受过trovir-naive的人类免疫缺陷病毒感染患者，旨在评估处方的洛匹那韦/利托那韦（800/200 mg qd或400/100 mg/bid）、司他夫定和拉米夫定的安全性、耐受性、药代动力学和抗病毒活性。本研究报告了考虑患者实际给药史的药代动力学分析。在第3周进行了洛匹那韦血浆浓度的密集采样，并在接下来的12个月内测量了4个额外的给药前（谷）浓度。使用电子监测报告的时间，通过将具有一级吸收和消除的简单单室药代动力学模型拟合至稀疏采样数据来实现收敛。相比之下，当假设处于稳态时，使用简单模型无法实现收敛，并且将患者报告的qd剂量丢失或最后2个bid剂量的时间用作模型输入。然后将估计的个体药代动力学参数与电子给药历史相结合，以预测每个患者的内部药物暴露时间过长。这一策略可能为大大提高常规治疗药物监测的信息产量和实用性提供基础。
Pharmacokinetic studies rely on blood sampling at times relative to predefined dosing intervals. Intensive sampling is often done under direct observation of dose taking, which, though costly, virtually eliminates uncertainty about actual dosing times. In contrast, the sparse sampling done in population pharmacokinetic studies relies on patient-reported times of dosing the accuracy of which the authors sought to assess by adding electronic monitoring to the usual patient reporting of closing times. The study involved 35 an tire troviral-naive, human immunodeficency virus-infected patients and was designed to assess the safety, tolerability, pharmacokinetics, and antiviral activity of prescribed lopinavir/ritonavir (800/200 mg qd or 400/100 mg/bid), stavudine, and lamivudine. The present research reports the pharmacokinetic analysis that results from taking into account the patients' actual dosing histories. Intensive sampling for plasma lopinavir concentrations was done at week 3, and 4 additional predose (trough) concentrations were measured during the next 12 months. Convergence was achieved by fitting a simple 1-compartment pharmacokinetic model, with first-order absorption and elimination, to the sparse sampling data, using electronic monitoring-reported times. In contrast, convergence was not achieved using the simple model when steady state was assumed, and the times for the lost qd dose or the last 2 bid doses, as reported by the patient, were used as model input. Estimated individual pharmacokinetic parameters were then combined with electronic dosing histories to project each patient's internal drug exposure overlong periods of time. This strategy may provide a basis for greatly increasing the informational yield and utility of conventional therapeutic drug monitoring.