Application of Target-Mediated Drug Disposition Model to Small Molecule Heat Shock Protein 90 Inhibitors

被引:22
|
作者
Yamazaki, Shinji [1 ]
Shen, Zhongzhou [1 ]
Jiang, Ying [1 ]
Smith, Bill J. [1 ]
Vicini, Paolo [1 ]
机构
[1] Pfizer Worldwide Res & Dev, Pharmacokinet Dynam & Metab, San Diego, CA 92121 USA
关键词
TUMOR-GROWTH INHIBITION; BREAST-CANCER MODELS; HSP90; INHIBITOR; PHARMACOKINETIC MODEL; BIOMARKER RESPONSE; MOUSE MODEL; CHAPERONE; PHARMACODYNAMICS; THERAPY; COMPLEX;
D O I
10.1124/dmd.113.051490
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Replacement of hydrogen with fluorine within three pairs of structurally similar small molecule inhibitors of heat shock protein 90 (HSP90) resulted in differences in inhibition constants (K-i) in vitro as well as marked differences in rat intravenous pharmacokinetic profiles. The difference in pharmacokinetic profiles between lower and higher affinity inhibitors (LAIs and HAIs, respectively) was characterized by remarkably different estimates for steady-state volumes of distribution (V-ss: 1.8-2.0 versus 10-13 l/kg) with comparable clearance estimates (3.2-3.5 l/h per kilogram). When the observed V-ss estimates were compared with the values predicted with the tissue-composition-based model, the observed V-ss estimates for HAIs were 4- to 8-fold larger than the predicted values, whereas the V-ss values for LAIs were comparable. Accordingly, a negative relationship between in vitro HSP90 K-i versus in vivo V-ss estimates was observed among these inhibitors. We therefore hypothesized that pharmacokinetic profiles of these inhibitors could be characterized by a target-mediated drug disposition (TMDD) model. In vivo equilibrium dissociation constant (K-D) estimates for HAIs due to target binding by TMDD model with rapid binding approximation were 1-6 nM (equivalent to 0.3-2 nM free drug), which appeared comparable to the in vitro K-i estimates (2-3 nM). In vivo K-D values of LAIs were not accurately determined by the TMDD model, likely due to nonspecific binding-dependent tissue distribution obscuring TMDD profiles. Overall, these results suggest that the observed large V-ss estimates for potent HSP90 inhibitors are likely due to pharmacological target binding.
引用
收藏
页码:1285 / 1294
页数:10
相关论文
共 50 条
  • [31] A Priori Identifiability of Target-Mediated Drug Disposition Models and Approximations
    Rena J. Eudy
    Matthew M. Riggs
    Marc R. Gastonguay
    The AAPS Journal, 2015, 17 : 1280 - 1284
  • [32] A Priori Identifiability of Target-Mediated Drug Disposition Models and Approximations
    Eudy, Rena J.
    Riggs, Matthew M.
    Gastonguay, Marc R.
    AAPS JOURNAL, 2015, 17 (05): : 1280 - 1284
  • [33] A mathematical analysis of rebound in a target-mediated drug disposition model: II. With feedback
    Philip J. Aston
    Gianne Derks
    Balaji M. Agoram
    Piet H. van der Graaf
    Journal of Mathematical Biology, 2017, 75 : 33 - 84
  • [34] Target-mediated drug disposition model: relationships with indirect response models and application to population PK–PD analysis
    Leonid Gibiansky
    Ekaterina Gibiansky
    Journal of Pharmacokinetics and Pharmacodynamics, 2009, 36 : 341 - 351
  • [35] Target-Mediated Drug Disposition Pharmacokinetic–Pharmacodynamic Model of Bosentan and Endothelin-1
    Anke-Katrin Volz
    Andreas Krause
    Walter Emil Haefeli
    Jasper Dingemanse
    Thorsten Lehr
    Clinical Pharmacokinetics, 2017, 56 : 1499 - 1511
  • [36] Quasi-Equilibrium Pharmacokinetic Model for Drugs Exhibiting Target-Mediated Drug Disposition
    Donald E. Mager
    Wojciech Krzyzanski
    Pharmaceutical Research, 2005, 22 : 1589 - 1596
  • [37] Dose correction for the Michaelis-Menten approximation of the target-mediated drug disposition model
    Yan, Xiaoyu
    Krzyzanski, Wojciech
    JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS, 2012, 39 (02) : 141 - 146
  • [38] Importance of Target-Mediated Drug Disposition (TMDD) of Small-Molecule Compounds and Its Impact on Drug Development-Example of the Class Effect of HSD-1 Inhibitors
    An, Guohua
    Katz, David A.
    JOURNAL OF CLINICAL PHARMACOLOGY, 2023, 63 (05): : 526 - 538
  • [39] Quasi-equilibrium pharmacokinetic model for drugs exhibiting target-mediated drug disposition
    Mager, DE
    Krzyzanski, W
    PHARMACEUTICAL RESEARCH, 2005, 22 (10) : 1589 - 1596
  • [40] A mathematical analysis of rebound in a target-mediated drug disposition model: II. With feedback
    Aston, Philip J.
    Derks, Gianne
    Agoram, Balaji M.
    van der Graaf, Piet H.
    JOURNAL OF MATHEMATICAL BIOLOGY, 2017, 75 (01) : 33 - 84