Effect of renal function on the pharmacokinetics of palifermin.

Palifermin (deltaN23KGF) decreases the incidence, severity, and duration of oral mucositis. The objectives of this open-label study were to evaluate the pharmacokinetics of single-dose palifermin in subjects with varying degrees of renal function. A single 90-mcg/kg intravenous dose of palifermin was administered to 31 subjects with varying levels of renal function (normal to requiring hemodialysis). Pharmacokinetic analyses were conducted using serum palifermin concentrations. There was considerable overlap in mean palifermin serum clearance among the groups, ranging from 318 to 495 mL/h/kg, indicating that the level of renal function did not affect clearance in humans; thus, no dose adjustment of palifermin is indicated for patients with renal dysfunction.

Evaluation of a minimal experimental design for determination of enzyme kinetic parameters and inhibition mechanism.

The advent of combinatorial chemistry has led to a deluge of new chemical entities whose metabolic pathways need to be determined. A significant issue involves determination of the ability of new agents to inhibit the metabolism of existing drugs as well as its own susceptibility for altered metabolism. There is need to estimate the enzyme inhibition parameters and mechanism or mechanisms of inhibition with minimal experimental effort. We examined a minimal experimental design for obtaining reliable estimates of K(i) (and V(max) and K(m)). Simulations have been applied to a variety of experimental scenarios. The least experimentally demanding case involved three substrate concentrations, [S], for the control and one substrate-inhibitor pair, [S]-[I]. The control and inhibitor data (with 20% coefficient of variance random error) were simultaneously fit to the full nonlinear competitive inhibition equation [simultaneous nonlinear regression (SNLR)]. Excellent estimates of the correct kinetic parameters were obtained. This approach is clearly limited by the a prior assumption of mechanism. Further simulations determined whether SNLR would permit assessment of the inhibition mechanism (competitive or noncompetitive). The minimal design examined three [S] (control) and three [S]-[I] pairs. This design was successful in identifying the correct model for 98 of 100 data sets (20% coefficient of variance random error). SNLR analysis of metabolite formation rate versus [S] permits a dramatic reduction in experimental effort while providing reliable estimates of K(i), K(m), and V(max) along with an estimation of the mechanism of inhibition. The accuracy of the parameter estimates will be affected by the experimental variability of the system under investigation.

Estimation of Ki in a competitive enzyme-inhibition model: comparisons among three methods of data analysis.

There are a variety of methods available to calculate the inhibition constant (Ki) that characterizes substrate inhibition by a competitive inhibitor. Linearized versions of the Michaelis-Menten equation (e.g., Lineweaver-Burk, Dixon, etc.) are frequently used, but they often produce substantial errors in parameter estimation. This study was conducted to compare three methods of analysis for the estimation of Ki: simultaneous nonlinear regression (SNLR); nonsimultaneous, nonlinear regression, "KM,app" method; and the Dixon method. Metabolite formation rates were simulated for a competitive inhibition model with random error (corresponding to 10% coefficient of variation). These rates were generated for a control (i.e., no inhibitor) and five inhibitor concentrations with six substrate concentrations per inhibitor and control. The KM/Ki ratios ranged from less than 0.1 to greater than 600. A total of 3 data sets for each of three KM/Ki ratios were generated (i.e., 108 rates/data set per KM/Ki ratio). The mean inhibition and control data were fit simultaneously (SNLR method) using the full competitive enzyme-inhibition equation. In the KM,app method, the mean inhibition and control data were fit separately to the Michaelis-Menten equation. The SNLR approach was the most robust, fastest, and easiest to implement. The KM,app method gave good estimates of Ki but was more time consuming. Both methods gave good recoveries of KM and VMAX values. The Dixon method gave widely ranging and inaccurate estimates of Ki. For reliable estimation of Ki values, the SNLR method is preferred.

Simultaneous quantitative analysis of methyl salicylate, ethyl salicylate and salicylic acid from biological fluids using gas chromatography-mass spectrometry.

A gas chromatographic-mass spectrometric (GC-MS) assay was developed for the quantitative analysis of methyl salicylate (MeS), ethyl salicylate (ES) and salicylic acid (SA) from biological fluids. The method was validated from 100-microl rat liver homogenate preparations (5 mg/ml protein) in 70 mM KH2PO4 (pH 7.4) buffer and from 100 microl rat plasma. The samples were extracted with chloroform, derivatized with BSTFA and quantitated by GC-MS in the SIM mode. The standard curves ranged from 31 ng/ml to 800 or 1250 ng/ml. Relative standard deviations and bias were less than 11% in plasma and homogenate for all compounds except SA which evidenced greater variability. The assay was used in preliminary experiments to characterize the pharmacokinetics of MeS in rats.