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用于疾病建模的环状/增殖系统中药物作用的基本 PK/PD 原理。

Basic PK/PD principles of drug effects in circular/proliferative systems for disease modelling.

机构信息

Exprimo NV, Zwaanstraatje 4, 2800, Mechelen, Belgium.

出版信息

J Pharmacokinet Pharmacodyn. 2010 Apr;37(2):157-77. doi: 10.1007/s10928-010-9151-7. Epub 2010 Mar 4.

Abstract

Disease progression modelling can provide information about the time course and outcome of pharmacological intervention on the disease. The basic PK/PD principles of proliferative and circular systems within the context of modelling disease progression and the effect of treatment thereupon are illustrated with the goal to better understand/predict eventual clinical outcome. Circular/proliferative systems can be very complex. To facilitate the understanding of how a dosing regimen can be defined in such systems we have shown the derivation of a system parameter named the Reproduction Minimum Inhibitory Concentration (RMIC) which represents the critical concentration at which the system switches from growth to extinction. The RMIC depends on two parameters (RMIC = (R(0) - 1) x IC(50)): the basic reproductive ratio (R(0)) a fundamental parameter of the circular/proliferative system that represents the number of offspring produced by one replicating species during its lifespan, and the IC(50), the potency of the drug to inhibit the proliferation of the system. The RMIC is constant for a given system and a given drug and represents the lowest concentration that needs to be achieved for eradication of the system. When exposure is higher than the RMIC, success can be expected in the long term. Time varying inhibition of replicating species proliferation is a natural consequence of the time varying inhibitor drug concentrations and when combined with the dynamics of the circular/proliferative system makes it difficult to predict the eventual outcome. Time varying inhibition of proliferative/circular systems can be handled by calculating the equivalent effective constant concentration (ECC), the constant plasma concentration that would give rise to the average inhibition at steady state. When ECC is higher than the RMIC, eradication of the system can be expected. In addition, it is shown that scenarios that have the same steady state ECC whatever the dose, dosage schedule or PK parameters have also the same average R (0) in the presence of the inhibitor (i.e. R (0-INH)) and therefore lead to the same outcome. This allows predicting equivalent active doses and dosing schedules in circular and proliferative systems when the IC(50) and pharmacokinetic characteristics of the drugs are known. The results from the simulations performed demonstrate that, for a given system (defined by its RMIC), treatment success depends mainly on the pharmacokinetic characteristics of the drug and the dosing schedule.

摘要

疾病进展建模可以提供关于疾病的药物干预时间过程和结果的信息。本文以增殖和循环系统的基本 PK/PD 原理为背景,阐述了疾病进展和治疗效果的建模,目的是更好地理解/预测最终的临床结果。循环/增殖系统可能非常复杂。为了帮助理解如何在这些系统中定义给药方案,我们展示了系统参数繁殖最小抑菌浓度 (RMIC) 的推导,它代表了系统从生长到灭绝的临界点。RMIC 取决于两个参数(RMIC = (R(0) - 1) x IC(50)):基本繁殖比 (R(0)),它是循环/增殖系统的一个基本参数,表示一个复制物种在其寿命期间产生的后代数量,以及 IC(50),即药物抑制系统增殖的效力。对于给定的系统和药物,RMIC 是常数,代表系统需要达到的最低浓度才能被清除。当暴露水平高于 RMIC 时,长期来看成功是可以预期的。复制物种增殖的时变抑制是时变抑制剂药物浓度的自然结果,当与循环/增殖系统的动力学结合时,很难预测最终结果。增殖/循环系统的时变抑制可以通过计算等效有效恒定浓度 (ECC) 来处理,即会导致平均稳态抑制的恒定血浆浓度。当 ECC 高于 RMIC 时,可以预期系统被清除。此外,还表明,无论剂量、给药方案或 PK 参数如何,只要稳态 ECC 相同的方案,在抑制剂存在下(即 R(0-INH))也具有相同的平均 R(0),因此会产生相同的结果。这允许在已知药物的 IC(50)和药代动力学特征的情况下,预测循环和增殖系统中的等效有效剂量和给药方案。所进行的模拟结果表明,对于给定的系统(由其 RMIC 定义),治疗成功主要取决于药物的药代动力学特征和给药方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4e/2861178/a9290617b811/10928_2010_9151_Fig1_HTML.jpg

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