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This research aims to provide scientific and effective sampling scheme for population pharmacokinetic (PK) study of amlodipine in patients with renal impairment and hypertension, provide a scientific method for an optimum design in clinical population PK/PD (pharmacodynamics) research. Brad Reisfeld1,2, Weihsueh Chiu3, Nan-Hung Hsieh3, Catherine Olschanowsky4, Frederic Bois5. Therefore, we select scheme 3 as the final sample scenario because it has good accuracy and precision and less sample points. There is no significant difference in MPE and MAPE of volume among them. MPE is 0.1% for scheme 6 and -0.6% for scheme 3, respectively. Among the 6 schemes, schemes 6 and 3 have good accuracy and precision. Finally, the accuracy and precision of the estimated parameters were evaluated using the mean prediction error (MPE) and the mean absolute error (MAPE), respectively. All modeling and simulation exercises were conducted with NONMEM version 7.2. Third, the estimation of amlodipine pharmacokinetic parameters (clearance (CL/F), volume (V/F) and Ka) was based on the simulation results. Second, we created a NONMEM-formatted dataset (n = 400) for each sample scenario via Monte Carlo simulation.
Nonmem nan software#
First, optimized sample scenarios were designed using WinPOPT software according to the aim, dosage regimen and visit schedule of the clinical study protocol, and the amlodipine population model reported by Rohatagi et al. We designed the sampling scheme for amlodipine based on D-optimal sampling strategy and Bayesian estimation method. It is an effective method for estimation of population pharmacokinetic parameters with sparse data to perform population pharmacokinetic analysis using the nonlinear mixed-effects models.
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Reasonable sampling scheme is the important basis for establishing reliable population pharmacokinetic model.