School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907, USA.
Pharmacotherapy. 2013 Jul;33(7):727-35. doi: 10.1002/phar.1267. Epub 2013 Apr 3.
To demonstrate the premise of individualized dosing charts (IDCs) as a clinical-bedside decision-support tool to individualize dosage regimens for drugs in which the interpatient variability is controlled by the pharmacokinetic (PK) behavior of the patient, to calculate the optimal sampling schedule (OSS), which minimizes the number of blood samples per patient. The approach is illustrated with available PK data for gabapentin.
Retrospective proof of principles study using gabapentin PK data from a published clinical trial.
Nineteen subjects in a trial designed to uncover the importance of the genetic contributions to variability in gabapentin absorption, renal elimination, and transport; subjects were monitored for 36 hours after administration of a single dose of gabapentin 400 mg, and plasma concentrations were determined at 14 time points.
When the PK profiles were different between subjects, the IDCs are dramatically different from each other and from the IDC for an "average" patient representing the patient population. The dose amount and dosing interval must be adjusted to maximize the probability of staying within the target concentration range. An optimal sampling methodology based on the assumption-free Bayesian approach is used to distinguish the PK profile of an individual patient from the patient population. In the case of gabapentin, only two optimally selected test blood samples, at 1.5 and 6 hours after administration of a single doses, were necessary. The average sensitivity and the average specificity of the OSS was 99% and 96%, respectively.
IDCs display the risk of a patient violating the target concentration range for any dosage regimen. They can be used as a clinical-bedside decision-support tool in a patient-physician partnership to decide on a dose amount and dosing interval that are medically acceptable while practical and convenient to ensure compliance. By using the assumption-free Bayesian approach and the OSS, the number of samples required from a new patient to individualize the dosage regimen can be reduced significantly while preserving high levels of sensitivity and specificity. Prospective studies are being planned to validate the encouraging results. This approach can be extended to any drug if PK data and a target concentration range are available for either therapeutic drug monitoring or target concentration intervention.
展示个体化剂量图（IDC）作为一种临床床边决策支持工具的前提，以针对患者药代动力学（PK）行为控制的药物个体化剂量方案，计算优化采样方案（OSS），使每个患者的血样数量最小化。该方法通过现有的加巴喷丁 PK 数据进行说明。
使用已发表临床试验中的加巴喷丁 PK 数据进行回顾性原理验证研究。
一项旨在揭示加巴喷丁吸收、肾清除和转运中遗传变异重要性的试验中的 19 名受试者；受试者在单次给予 400mg 加巴喷丁后 36 小时内进行监测，并在 14 个时间点测定血浆浓度。
当受试者之间的 PK 曲线不同时，IDC 彼此之间以及与代表患者人群的“平均”患者的 IDC 有很大差异。剂量和给药间隔必须调整，以最大限度地提高维持目标浓度范围内的概率。基于无假设贝叶斯方法的最佳采样方法用于将个体患者的 PK 曲线与患者人群区分开来。在加巴喷丁的情况下，仅需两次最佳选择的测试血样，即在单次剂量后 1.5 和 6 小时。最佳采样方案的平均灵敏度和平均特异性分别为 99%和 96%。
IDC 显示患者违反任何剂量方案目标浓度范围的风险。它们可以作为一种临床床边决策支持工具，在患者-医生合作中使用，以确定可接受的剂量和给药间隔，既符合医学要求又方便实用，以确保依从性。通过使用无假设贝叶斯方法和 OSS，可以在保留高灵敏度和特异性的同时，大大减少为个体化剂量方案从新患者采集样本的数量。正在计划进行前瞻性研究以验证令人鼓舞的结果。如果有 PK 数据和目标浓度范围，可将此方法扩展到任何药物，用于治疗药物监测或目标浓度干预。
