title: A Nonparametric Alternative to Modeling Population Pharmacokinetics in Patients with Spinal Cord Injury: Comparison with the Standard Two-Stage Method.
abstract: 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.
authors.affiliation: Medical and Spinal Cord Injury Service, Department of Veterans Affairs Medical Center, Long Beach, USA, and Department of Medicine, University of California, Irvine, USA.
authors.forename: Jack L.
authors.initials: JL
authors.lastname: Segal
authors.forename: Thomas M.
authors.initials: TM
authors.lastname: Gilman
authors.forename: Sherry R.
authors.initials: SR
authors.lastname: Brunnemann