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10.1124/dmd.114.058297 http://scihub22266oqcxt.onion/10.1124/dmd.114.058297 C4152872!4152872!24939653     free     free     free Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 261.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Drug+Metab+Dispos 2014 ; 42 (9): 1587-95 Nephropedia Template TP {{tp|p=24939653|t=2014. A Numerical Method for Analysis of In Vitro Time-Dependent Inhibition Data Part 2 Application to Experimental Data |pdf=|usr=}}{{24939653}} gab.com Text A Numerical Method for Analysis of In Vitro Time-Dependent Inhibition Data Part 2 Application to Experimental Data JO: Drug Metab Dispos http://www.kidney.de/pget.php?&tw=1&pmid=24939653 #FOAvip Time-dependent inhibition (TDI) of cytochrome P450 enzymes is an important cause of drug-drug interactions. The standard approach to characterize the kinetics of TDI is to determine the rate of enzyme loss, kobs, at various inhibitor concentrations, [I], and replot the kobs versus [I] to obtain the key kinetic parameters, KI and kinact. In our companion manuscript (Part 1; Nagar et al., 2014) in this issue of Drug Metabolism and Disposition, we used simulated datasets to develop and test a new numerical method to analyze in vitro TDI data. Here, we have applied this numerical method to five TDI datasets. Experimental datasets include the inactivation of CYP2B6, CYP2C8, and CYP3A4. None of the datasets exhibited Michaelis-Menten?only kinetics, and the numerical method allowed use of more complex models to fit each dataset. Quasi-irreversible as well as partial inhibition kinetics were observed and parameterized. Three datasets required the use of a multiple-inhibitor binding model. The mechanistic and clinical implications provided by these analyses are discussed. Together with the results in Part 1, we have developed and applied a new numerical method for analysis of in vitro TDI data. This method appears to be generally applicable to model in vitro TDI data with atypical and complex kinetic schemes. Twit Text FOAVip A Numerical Method for Analysis of In Vitro Time-Dependent Inhibition Data Part 2 Application to Experimental Data ????Drug Metab Dispos http://www.kidney.de/pget.php?&tw=1&pmid=24939653 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24939653 #FOAvip English Wikipedia <ref>{{Cite pmid|24939653}}</ref> A Numerical Method for Analysis of In Vitro Time-Dependent Inhibition Data Part 2 Application to Experimental Data #MMPMID24939653 Korzekwa K; Tweedie D; Argikar UA; Whitcher-Johnstone A; Bell L; Bickford S; Nagar S Drug Metab Dispos 2014[Sep]; 42 (9): 1587-95 PMID24939653show ga Time-dependent inhibition (TDI) of cytochrome P450 enzymes is an important cause of drug-drug interactions. The standard approach to characterize the kinetics of TDI is to determine the rate of enzyme loss, kobs, at various inhibitor concentrations, [I], and replot the kobs versus [I] to obtain the key kinetic parameters, KI and kinact. In our companion manuscript (Part 1; Nagar et al., 2014) in this issue of Drug Metabolism and Disposition, we used simulated datasets to develop and test a new numerical method to analyze in vitro TDI data. Here, we have applied this numerical method to five TDI datasets. Experimental datasets include the inactivation of CYP2B6, CYP2C8, and CYP3A4. None of the datasets exhibited Michaelis-Menten?only kinetics, and the numerical method allowed use of more complex models to fit each dataset. Quasi-irreversible as well as partial inhibition kinetics were observed and parameterized. Three datasets required the use of a multiple-inhibitor binding model. The mechanistic and clinical implications provided by these analyses are discussed. Together with the results in Part 1, we have developed and applied a new numerical method for analysis of in vitro TDI data. This method appears to be generally applicable to model in vitro TDI data with atypical and complex kinetic schemes. äA Numerical Method for Analysis of In Vitro Time-Dependent Inhibition (epmc).pdf DeepDyve Pubget Overpricing