PREDICTION OF DRUG INTERACTIONS IN VIVO AND IN VITRO

新陈代谢的体内外相关性研究进展 基于药物的相互作用表明，酶的行为在很大程度上 保守的。然而，目前预测抑制的方法 以此为基础的互动基本上保持了定性。对无数人来说 抑制剂，体外测定的抑制常数不足以 预测体内相互作用的程度。这些抑制剂似乎是 在体内比在体外更有效。在……领域的一个根本问题 体外-体内相关性是缺乏一种通用的方法学 获得酶位置的抑制物浓度和 在现场实际占优势的抑制常数。在现在 应用，我们将检验“免费药物假说”，即概念 这种抑制作用是由实际部位的非结合抑制物控制的 酶的活性。在前两个具体目标中，我们将证明 游离药物假说在体外对竞争性抑制剂有效 只要非结合浓度是使用广泛的 不同蛋白结合力和亲脂性的抑制剂名单 特点。具体目标2(A)和2(B)将检验 体内的“免费药物假说”。这将使用一个新的 参数，“抑制常数比”(R/KI)。理论表明， 这一比率(定义为K/I/(Pre)在纯化的重组体中确定 系统除以在体内确定的K/I/IV)将等于1，并且 它将不依赖于酶。因此，这项建议将提供一个有用的 从衍生数据中实现体内定量预测的框架 在试管中。

The recent successes of in vivo-in vitro correlations for metabolically based drug interactions suggests that enzyme behavior is largely conserved. However, current approaches to the prediction of inhibition based interactions have remained essentially qualitative. For numerous inhibitors, inhibition constants determined in vitro do not adequately predict the extent of interaction in vivo. These inhibitors appear to be more potent in vivo than in vitro. A fundamental problem in the field of in vitro-in vivo correlations is the absence of a general methodology for obtaining the concentration of inhibitor at the enzyme site and the inhibition constant that actually prevails at the site. In the present application, we will test the "free drug hypothesis," i.e. the concept that inhibitor effect is governed by unbound inhibitor at the actual site of the enzyme. In the first two specific aims, we will demonstrate that the free drug hypothesis is valid for competitive inhibitors in in vitro systems so long as unbound concentrations are measured using an extensive list of inhibitors with different protein binding and lipophilicity characteristics. Specific Aims 2(a) and 2(b) will test the validity of the "free drug hypothesis" in vivo. This will be accomplished using a new parameter, the "inhibition constants ratio" (R/kI). Theory suggests that this ratio (defined as K/i/(pre) determined in a purified recombinant system divided by the K/i/iv determined in vivo) will equal one and that it will be independent of enzyme. This proposal will thus provide a useful framework to effectuate quantitative in vivo predictions from data derived in vitro.