Proost J H
Department of Pharmacokinetics and Drug Delivery, University Centre for Pharmacy, Groningen, The Netherlands.
Int J Clin Pharmacol Ther. 1995 Oct;33(10):531-6.
Optimal drug therapy can only be achieved if a drug is given in the right dosage regimen. Therefore the dosage regimen needs to be optimized, using the available information of the drug, the patient, and his disease. The optimization of drug therapy comprises two major steps: First, the clinician should define explicit therapeutic goals for each patient individually. Second, a strategy to achieve these goals with the greatest possible precision should be chosen. An overview of the optimization of drug therapy is presented, with special reference to maximum a posteriori probability (MAP) Bayesian fitting. Drug dosage optimization requires 1. measurement of a performance index related to the therapeutic goal, generally one or more plasma concentration measurements, 2. population pharmacokinetic parameters, including mean values, standard deviations, covariances and information on the statistical distribution, and 3. reliable software for adaptive control strategy and optimal dosage regimen calculation. The benefit of optimal drug therapy by adaptive control using MAP Bayesian fitting has been proven, resulting in improved patient outcome by improved efficacy of therapy and a reduction of adverse reactions, and in reduced costs, mainly due to a reduction of hospitalization. Newer strategies might replace the MAP Bayesian fitting procedure, if their advantage has been demonstrated convincingly, and if reliable and user-friendly software is available.
只有以正确的给药方案给予药物，才能实现最佳药物治疗。因此，需要利用药物、患者及其疾病的现有信息来优化给药方案。药物治疗的优化包括两个主要步骤：首先，临床医生应为每个患者单独确定明确的治疗目标。其次，应选择一种尽可能精确地实现这些目标的策略。本文概述了药物治疗的优化，特别提及最大后验概率（MAP）贝叶斯拟合。药物剂量优化需要：1. 测量与治疗目标相关的性能指标，通常是一次或多次血浆浓度测量；2. 群体药代动力学参数，包括均值、标准差、协方差以及统计分布信息；3. 用于自适应控制策略和最佳给药方案计算的可靠软件。通过使用MAP贝叶斯拟合进行自适应控制实现最佳药物治疗的益处已得到证实，这带来了治疗效果改善、不良反应减少从而改善患者预后，以及成本降低，主要是由于住院次数减少。如果新策略的优势得到令人信服的证明，并且有可靠且用户友好的软件，那么更新的策略可能会取代MAP贝叶斯拟合程序。
