Stein A M, Ramakrishna R
Novartis Institute for BioMedical Research, Cambridge, Massachusetts, USA.
CPT Pharmacometrics Syst Pharmacol. 2017 Apr;6(4):258-266. doi: 10.1002/psp4.12169. Epub 2017 Apr 4.
For monoclonal antibody (mAb) drugs, soluble targets may accumulate several thousand fold after binding to the drug. Time course data of mAb and total target is often collected and, although free target is more closely related to clinical effect, it is difficult to measure. Therefore, mathematical models of this data are used to predict target engagement. In this article, a "potency factor" is introduced as an approximation for the model-predicted target inhibition. This potency factor is defined to be the time-Averaged Free target concentration to Initial target concentration Ratio (AFIR), and it depends on three key quantities: the average drug concentration at steady state; the binding affinity; and the degree of target accumulation. AFIR provides the intuition for how changes in dosing regimen and binding affinity affect target capture and AFIR can be used to predict the druggability of new targets and the expected benefits of more potent, second-generation mAbs.
对于单克隆抗体（mAb）药物，可溶性靶点与药物结合后可能会积累数千倍。通常会收集单克隆抗体和总靶点的时间进程数据，尽管游离靶点与临床疗效的关系更为密切，但难以测量。因此，利用这些数据的数学模型来预测靶点结合情况。在本文中，引入了一个“效价因子”作为模型预测靶点抑制的近似值。该效价因子定义为时间平均游离靶点浓度与初始靶点浓度之比（AFIR），它取决于三个关键量：稳态时的平均药物浓度、结合亲和力和靶点积累程度。AFIR为给药方案和结合亲和力的变化如何影响靶点捕获提供了直观理解，并且AFIR可用于预测新靶点的成药可能性以及更强效的第二代单克隆抗体的预期益处。
