A Nonparametric Alternative to Modeling Population Pharmacokinetics in Patients with Spinal Cord Injury: Comparison with the Standard Two-Stage Method.
The estimation of population-specific pharmacokinetic parameters from sparse of fragmentary data obtained during routine patient care is a powerful analytical tool in drug development and therapeutic drug monitoring. The Nonparametric Expectation Maximization program (NPEM) performs this function and generates robust parameter estimates which are distribution-free and unconstrained by assumption-rich parametric, for example, Gaussian, analyses. We compared standard two-stage method (STS) estimates of amikacin pharmacokinetic parameters (V, CL) derived from a sampling rich strategy (11 patients with spinal cord injury, SCI; 7 able-bodied controls) to estimates of pharmacokinetic parameters obtained from an NPEM one-compartment analysis incorporating the 11 optimally sampled SCI patients and 8 sparse data sets (19 patients with SCI; 7 controls). The STS (n = 11) and NPEM (n = 19) analyses provided similar V and CL parameter estimates in patients with SCI: 0.20 plus minus 0.04 L kg(minus sign1), 0.93 plus minus 0.24 ml min(minus sign1) kg(minus sign1) and 0.20 plus minus 0.06 L kg(minus sign1), 1.12 plus minus 0.26 ml min(minus sign1) kg(minus sign1), respectively. NPEM is a useful, user-friendly, distribution-free computational program for estimating the central tendency and interindividual variability of amikacin pharmacokinetic parameters in spinal cord injured humans.
Segal
Jack L.
JL
Medical and Spinal Cord Injury Service, Department of Veterans Affairs Medical Center, Long Beach, USA, and Department of Medicine, University of California, Irvine, USA.
Gilman
Thomas M.
TM
Brunnemann
Sherry R.
SR