Estimation of Theophylline Clearance During Intravenous Aminophylline Infusions

A New Definition of Pharmaceutical Quality: Assembly of a Risk Simulation Platform to Investigate the Impact of Manufacturing/ Product Variabcpility on Clinical Performance

“…Analogous to clearance, the volume of distribution was assumed to be constant for each patient during the course of simulated therapy. The application of invariant clearances and volumes of distribution is commensurate with previous published studies 8–10…”

“…Volume of distribution was assigned by randomly sampling a normal distribution defined by a mean volume of distribution of 0.47 L/kg and a standard deviation of 0.03 L/kg. While previous studies have assumed one (constant) average volume of distribution for all patients (e.g., 0.45 L/kg),8, 9 the authors considered this to be more representative of the variability that would be encountered in actual patients. The volume of distribution values for the 100,000‐patient population are shown in Figure 3.…”

“…Since multiple dosages were administered throughout the course of therapy, the principle of superposition was applied 22. The superposition principle assumes that the pharmacokinetics of the drug are not dose‐dependent and that the drug is eliminated by first‐order kinetics, which are reasonable assumptions for the administration of theophylline 9, 10, 14–21. The change in theophylline plasma concentration as a function of time was modeled using the equation where C p is the theophylline plasma concentration (mg/L), t is the time (h), S is the optional scaling factor, D is the dose (mg), V d is the volume of distribution (L/kg), W is the patient's total body weight (kg), β is the Weibull shape parameter, α is the Weibull time constant (h), A is the IVIVC scale factor, P is the IVIVC power law parameter, and Cl is clearance (mL/kg/h).…”

An Updated Comparison of Drug Dosing Methods

“…In 19 of the 22 nonsmoking outpatients, the Bayesian method accurately predicted steady-state trough theophylline concentrations [mean error (± SD): -0.6 ± 2.1 mg/L]. Gilman et al (1985) compared the a priori methods of Jusko et al (1979) and Powell et al (1978), the algebraic method of Chiou et al (1978), and a Bayesian least squares regression method for their ability in predicting theophylline clearance in 16 patients. Imaeda et al (1988) studied the use of a Bayesian method (MVL TI 2 BAYES, Yamaoka et al 1985) for its ability to predict pharmacokinetic parameters and theophylline concentrations in 7 patients.…”