Yim Dong-Seok
Department of Clinical Pharmacology and Therapeutics, The Catholic University of Korea, Seoul St. Mary's Hospital, Seoul 06591, Korea.
PIPET (Pharmacometrics Institute for Practical Education and Training), College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.
Korean J Physiol Pharmacol. 2019 Jul;23(4):231-236. doi: 10.4196/kjpp.2019.23.4.231. Epub 2019 Jun 25.
In drug discovery or preclinical stages of development, potency parameters such as IC, , or have been routinely used to predict the parameters of efficacious exposure (AUC, , etc.) in humans. However, to our knowledge, the fundamental assumption that the potency is correlated with the efficacious concentration in humans has not been investigated extensively. Thus, the present review examined this assumption by comparing a wide range of published pharmacokinetic (PK) and potency data. If the drug potency and its effectiveness in humans are well correlated, the steady-state average unbound concentrations in humans [ = ·F·Dose/(·τ) = ·AUCss/τ] after treatment with approved dosage regimens should be higher than, or at least comparable to, the potency parameters assessed . We reviewed the ratios of /potency for a total of 54 drug entities (13 major therapeutic classes) using the dosage, PK, and potency reported in the published literature. For 54 drugs, the / potency ratios were < 1 for 38 (69%) and < 0.1 for 22 (34%) drugs. When the ratios were plotted against (unbound fraction), "ratio < 1" was predominant for drugs with high protein binding (90% of drugs with ≤ 5%; i.e., 28 of 31 drugs). Thus, predicting the efficacious unbound concentrations in humans using only potency data and should be avoided, especially for molecules with high protein binding.
在药物研发或临床前开发阶段，诸如IC、 或 等效力参数通常被用于预测人体有效暴露参数（AUC、 等）。然而，据我们所知，效力 与人体有效浓度 相关这一基本假设尚未得到广泛研究。因此，本综述通过比较大量已发表的药代动力学（PK）和效力数据来检验这一假设。如果药物效力 与其在人体中的有效性具有良好的相关性，那么按照批准的给药方案治疗后，人体中的稳态平均非结合浓度[ = ·F·剂量/(·τ) = ·AUCss/τ]应高于或至少与所评估的效力参数相当。我们使用已发表文献中报道的剂量、PK和效力，回顾了总共54种药物实体（13个主要治疗类别）的 /效力比值。对于54种药物，38种（69%）的 /效力比值<1，22种（34%）药物的该比值<0.1。当将这些比值与 （非结合分数）作图时，对于高蛋白结合药物（ ≤ 5%的药物中的90%；即31种药物中的28种），“比值<1”占主导。因此，应避免仅使用效力数据和 来预测人体中的有效非结合浓度，尤其是对于高蛋白结合的分子。
