Performance of FOCEI vs SAEM in simple population pharmacokinetic analysis of rich, medium and sparse data.
Waroonrat Sukarnjanaset (1), Thitima Wattanavijitkul (1), Sutep Jarurattanasirikul (2)
(1) Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand (2) Department of Medicine, Faculty of Medicine, Prince of Songkla University, Songkla, Thailand
Objectives: To evaluate the performance (accuracy, precision, completion rates, and runtimes) of FOCEI and SAEM estimation methods in population pharmacokinetic (PK) analysis using NONMEM® when implemented with a one compartment model across rich, medium and sparse sampling data.
Methods: Three types of data (rich, medium and sparse) were explored. For each scenario, 100 datasets were simulated for 100 patients using a one compartment model from previously published results.[1] The simulated data below the limit of quantification of 0.5 mg/L were removed from the datasets. Every dataset was separately estimated with FOCEI and SAEM methods using the same initial estimates. The simulation and estimation were conducted using NONMEM® 7.3 under Windows 7 Enterprise 64-bit operating system. The percentage of relative estimation error (RER) and root mean square error (RMSE) were calculated to assess the accuracy and precision of parameter estimates. The completion rates and runtimes were also compared.
Results: Across the three scenarios, FOCEI and SAEM provided the same completion rate of 100% and both methods accurately and precisely estimated all PK parameters. RERs and RMSEs were comparable. Median RERs were within ±5% and ±10% for fixed and random effect parameters, respectively. For all scenarios, both methods had RMSE < 1.5 and 0.03 for fixed and random effect parameters, respectively. However, the run times were shorter with FOCEI (ranged from 9 to 25 seconds) compared to SAEM (ranged from 215 to 811 seconds).
Conclusions: In simple population PK analysis, FOCEI could provide accurate and precise PK parameter estimates across rich, medium and sparse data similar to SAEM but with shorter run times.
References:
[1] Chen R, Qian Q, Sun MR, Qian CY, Zou SL, Wang ML, et al. Population pharmacokinetics and pharmacodynamics of Piperacillin/Tazobactam in patients with nosocomial infections. Eur J Drug Metab Pharmacokinet. (2016) 41(4):363-72.
