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[如何测量药物生物效应的动力学]

[How to measure the kinetics of biological effect of a drug].

作者信息

Lechat P, Canet E

机构信息

Pharmacologie Clinique, Groupe Hospitalier, Pitié Salpetrière, Paris, France.

出版信息

Therapie. 1997 Jul-Aug;52(4):291-8.

PMID:9437880
Abstract

Therapeutic benefit that can be induced by a pharmaceutical compound partly relies upon the profile of its biological action. Evaluation of the drug-induced effect profile in a given pathological condition begins with the determination of the relevant biological effect related to the therapeutic benefit, which is not always obvious. Evaluation itself is based on dose-effect relationships as a function of time. During chronic treatment, such a kinetic profile oscillates between peak and trough levels. Relationships that can be established between time-dependent effect profile and pharmacokinetic data lead to PK-PD mathematical model, whose main objectives are simulation, prediction of effect and ultimately dose optimisation. The therapeutic implications of the time-dependent effect profile are well illustrated in the cases of antibiotics, diuretics such as furosemide and anti-hypertensive drugs. During drug development, PK-PD approaches can be used in the initial clinical and even pre-clinical phases and can lead to a better definition of effective dose ranges, optimisation of large scale clinical trials or identification of high risk patients. This may favour a reduction of costs and duration of development. Validation of such an approach is easier in well known therapeutic domains but can be more difficult with innovative drugs. The implications of PK-PD approaches can however, be, limited when the relevant biological or clinical parameter cannot be assessed, when the cascade of events leading to pharmacological and therapeutic effects is complex or finally when such PK-PD models require a long time to be established during the early phase of drug development.

摘要

药物化合物所诱导的治疗益处部分取决于其生物作用特征。在特定病理状况下评估药物诱导的效应特征,始于确定与治疗益处相关的相关生物效应,而这并非总是显而易见的。评估本身基于作为时间函数的剂量 - 效应关系。在慢性治疗期间,这种动力学特征在峰值和谷值水平之间波动。时间依赖性效应特征与药代动力学数据之间可建立的关系导致了药代动力学 - 药效学(PK - PD)数学模型,其主要目标是模拟、效应预测以及最终的剂量优化。时间依赖性效应特征的治疗意义在抗生素、呋塞米等利尿剂以及抗高血压药物的案例中得到了很好的体现。在药物研发过程中,PK - PD 方法可用于初始临床甚至临床前阶段,并可导致更明确有效剂量范围、优化大规模临床试验或识别高风险患者。这可能有利于降低成本和缩短研发时间。在知名治疗领域验证这种方法更容易,但对于创新药物可能更困难。然而,当相关生物或临床参数无法评估、导致药理和治疗效应的事件级联复杂或者最终当此类 PK - PD 模型在药物研发早期需要很长时间才能建立时,PK - PD 方法的影响可能会受到限制。

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