School of Pharmacy, Ohio State University, 500 12th West Avenue, Columbus, OH 43210, USA.
J Pharmacokinet Pharmacodyn. 2011 Feb;38(1):83-104. doi: 10.1007/s10928-010-9179-8. Epub 2010 Dec 17.
Drug kinetics in human has been studied from both deterministic and stochastic perspectives. However, little research has been done to systematically determine the probability for a drug molecule to follow a specific traveling route. Recently a method was developed to estimate this probability and the probability density function of residence time in linear systems. In this paper, we provide a rigorous proof of the main results of the previous paper and extend the method to nonlinear multi-compartment systems. A novel concept of compartment expansion is introduced to facilitate the development of our method. This formulation resolves computational difficulties associated with nonlinear systems, allowing for direct estimation of the probability intensity coefficients, and subsequently the transition probability and probability density function of the residence time. With such expansion of the methodology, it becomes both practical and feasible to apply it in the real-world drug development where drug disposition patterns are often nonlinear. The method can be used to estimate drug exposure at any site of interest, thus may help us to gain better understanding about the impact of drug exposure on efficacy and safety.
已经从确定性和随机性两个角度研究了人体中的药物动力学。然而，很少有研究系统地确定药物分子遵循特定行进路线的概率。最近，已经开发出一种估计这种概率的方法，以及在线性系统中停留时间的概率密度函数。在本文中，我们为前一篇论文的主要结果提供了严格的证明，并将该方法扩展到非线性多室系统。引入了一种新的隔室扩展概念，以方便我们方法的发展。这种表述解决了与非线性系统相关的计算难题，允许直接估计概率强度系数，从而可以直接估计转移概率和停留时间的概率密度函数。通过这种方法的扩展，它在药物开发的实际应用中变得既实际又可行，在药物处置模式通常是非线性的情况下。该方法可用于估计任何感兴趣部位的药物暴露量，从而有助于我们更好地了解药物暴露对疗效和安全性的影响。
