Population pharmacodynamics of cilostazol in healthy Korean subjects

Cilostazol is used for the treatment of intermittent claudication, ulceration and pain. This study was conducted to develop a population pharmacodynamic (PD) model for cilostazol's closure time (CT) prolongation effect in healthy Korean subjects based on a pharmacokinetic (PK) model previously developed. PD data were obtained from 29 healthy subjects who participated in a study conducted in 2009 at Severance Hospital. The PK model used was a two-compartment model with first order absorption. CT data were best described by a turnover model with a fractional turnover rate constant (K(out)) inhibited by drug effects (Eff), which were represented by a sigmoid E(max) model [Eff = E(max) · C(γ) / (EC₅₀(γ)+C(γ))] with E(max) being maximum drug effect, EC₅₀ drug plasma concentration at 50% of E(max), C drug plasma concentrations, and γ the Hill coefficient. For the selected PD model, parameter estimates were 0.613 hr⁻¹ for K(out), 0.192 for E(max), 730 ng/ml for EC₅₀ and 5.137 for γ. Sex and caffeine drinking status significantly influenced the baseline CT, which was 85.36 seconds in male non-caffeine drinkers and increased by 15.5% and 16.4% in females and caffeine drinkers, respectively. The model adequately described the time course of CT. This was the first population PD study for cilostazol's CT prolongation effect in a Korean population.

Parameter estimation for sigmoid E(max) models in exposure-response relationship

The purpose of this simulation study is to explore the limitation of the population PK/PD analysis using data from a clinical study and to help to construct an appropriate PK/PD design that enable precise and unbiased estimation of both fixed and random PD parameters in PK/PD analysis under different doses and Hill coefficients. Seven escalating doses of virtual drugs with equal potency and efficacy but with five different Hill coefficients were used in simulations of single and multiple dose scenarios with dense sampling design. A total of 70 scenarios with 100 subjects were simulated and estimated 100 times applying 1-compartment PK model and sigmoid E(max) model. The bias and precision of the parameter estimates in each scenario were assessed using relative bias and relative root mean square error. For the single dose scenarios, most PD parameters of sigmoid E(max) model were accurately and precisely estimated when the C(max) was more than 85% of EC₅₀, except for typical value and inter-individual variability of EC₅₀ which were poorly estimated at low Hill coefficients. For the multiple dose studies, the parameter estimation performance was not good. This simulation study demonstrated the effect of the relative range of sampled concentrations to EC₅₀ and sigmoidicity on the parameter estimation performance using dense sampling design.