Straube Ronny
Pioneering Medicines, Cambridge, Massachusetts, USA.
CPT Pharmacometrics Syst Pharmacol. 2025 Jul;14(7):1262-1272. doi: 10.1002/psp4.70048. Epub 2025 May 27.
Target-mediated drug disposition (TMDD) is often associated with high-affinity binding to a target resulting in nonlinear pharmacokinetics. For large molecules, such as monoclonal antibodies, this can lead to increased clearance at sub-saturating concentrations. However, for small molecules, target binding can protect the drug from a fast systemic clearance. Here, we show that both types of behaviors can be described by simple expressions arising from a high-affinity approximation of the standard TMDD model. Interestingly, the celebrated Michaelis-Menten (MM) approximation arises in the opposite limit of low affinity and if the systemic drug clearance is sufficiently slow. Our derivation contains a previously missing factor in front of the MM constant that becomes important when target and drug-target complex elimination rates are different. As a measure of target suppression, we also derive simple expressions for the free target to baseline ratio and compare our approximations with data from large and small molecules.
靶点介导的药物处置(TMDD)通常与对靶点的高亲和力结合相关,从而导致非线性药代动力学。对于大分子,如单克隆抗体,这可能导致在亚饱和浓度下清除率增加。然而,对于小分子,靶点结合可以保护药物免于快速的全身清除。在这里,我们表明这两种行为都可以用标准TMDD模型的高亲和力近似产生的简单表达式来描述。有趣的是,著名的米氏(MM)近似出现在低亲和力的相反极限情况下,并且当全身药物清除率足够慢时。我们的推导在MM常数前面包含一个先前缺失的因子,当靶点和药物-靶点复合物的消除速率不同时,这个因子变得很重要。作为靶点抑制的一种度量,我们还推导了游离靶点与基线比值的简单表达式,并将我们的近似值与大分子和小分子的数据进行比较。