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首页> 美国卫生研究院文献>Springer Open Choice >Basic PK/PD principles of drug effects in circular/proliferative systems for disease modelling
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Basic PK/PD principles of drug effects in circular/proliferative systems for disease modelling

机译：循环/增生系统中药物作用的基本PK / PD原理用于疾病建模

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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 = (R0 − 1) × IC50): the basic reproductive ratio (R0) a fundamental parameter of the circular/proliferative system that represents the number of offspring produced by one replicating species during its lifespan, and the IC50, 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 R0 in the presence of the inhibitor (i.e. R0-INH) and therefore lead to the same outcome. This allows predicting equivalent active doses and dosing schedules in circular and proliferative systems when the IC50 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.
机译：疾病进展建模可以提供有关该疾病的时程和药理干预结果的信息。为了更好地理解/预测最终的临床结果，举例说明了疾病和疾病发展过程中的增殖和循环系统的基本PK / PD原理及其治疗效果。循环/扩散系统可能非常复杂。为便于理解如何在此类系统中定义给药方案，我们展示了一个名为“生殖最小抑制浓度”（RMIC）的系统参数的推导，该参数表示系统从生长到灭绝的临界浓度。 RMIC取决于两个参数（RMIC =（R0−1）×IC50）：基本繁殖率（R0）是循环/增殖系统的基本参数，代表一个复制物种在其寿命内产生的后代数量，以及IC50是药物抑制系统增殖的效力。 RMIC对于给定的系统和给定的药物而言是恒定的，代表了根除系统所需达到的最低浓度。当暴露程度高于RMIC时，就长期而言有望取得成功。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，很难预测最终的结果。增殖/循环系统的时变抑制可通过计算等效有效恒定浓度（ECC）来处理，恒定等效血浆浓度会引起稳态下的平均抑制浓度。当ECC高于RMIC时，可以期望消除该系统。另外，表明在抑制剂存在下（R0-INH），无论剂量，给药方案或PK参数如何，具有相同稳态ECC的场景也具有相同的平均R0，因此导致相同的结果。当已知药物的IC50和药代动力学特征时，这可以预测循环和增殖系统中的等效活性剂量和给药方案。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。

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