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PubMed2004

Threshold-linear analysis of measures of fertility in artificial insemination data and days to calving in beef cattle.

Mating and calving records for 47,533 first-calf heifers in Australian Angus herds were used to examine the relationship between days to calving (DC) and two measures of fertility in AI data: 1) calving to first insemination (CFI) and 2) calving success (CS). Calving to first insemination and calving success were defined as binary traits. A threshold-linear Bayesian model was employed for both analyses: 1) DC and CFI and 2) DC and CS. Posterior means (SD) of additive covariance and corresponding genetic correlation between the DC and CFI were -0.62 d (0.19 d) and -0.66 (0.12), respectively. The corresponding point estimates between the DC and CS were -0.70 d (0.14 d) and -0.73 (0.06), respectively. These genetic correlations indicate a strong, negative relationship between DC and both measures of fertility in AI data. Selecting for animals with shorter DC intervals genetically will lead to correlated increases in both CS and CFI. Posterior means (SD) for additive and residual variance and heritability for DC for the DC-CFI analysis were 23.5 d2 (4.1 d2), 363.2 d2 (4.8 d2), and 0.06 (0.01), respectively. The corresponding parameter estimates for the DC-CS analysis were very similar. Posterior means (SD) for additive, herd-year and service sire variance and heritability for CFI were 0.04 (0.01), 0.06 (0.06), 0.14 (0.16), and 0.03 (0.01), respectively. Posterior means (SD) for additive, herd-year, and service sire variance and heritability for CS were 0.04 (0.01), 0.07 (0.07), 0.14 (0.16), and 0.03 (0.01), respectively. The similarity of the parameter estimates for CFI and CS suggest that either trait could be used as a measure of fertility in AI data. However, the definition of CFI allows the identification of animals that not only record a calving event, but calve to their first insemination, and the value of this trait would be even greater in a more complete dataset than that used in this study. The magnitude of the correlations between DC and CS-CFI suggest that it may be possible to use a multitrait approach in the evaluation of AI and natural service data, and to report one genetic value that could be used for selection purposes.

Animals↗

PubMed1986

The use of angular acoustic scattering measurements to estimate structural parameters of human and animal tissues.

Theoretical formulations are developed, based on mathematical models of inhomogeneous continua for the expected angular variation of bulk scattering from human and animal tissues. These results are compared with experimental data on angular scattering from liver, muscle, and blood, reported in a companion paper [J. Acoust. Soc. Am. 79, 2034-2047 (1986)], and deductions are drawn as to the appropriateness of the various models for representing the mechanical structure of the different tissues. On this basis, the experimental data and theoretical formulations are used to derive estimates, appropriate to the frequency range of observation (4-7 MHz), of correlation distance (or effective scatterer spacing) d, the local variabilities of density and compressibility, gamma rho = delta rho/rho and gamma kappa = delta kappa/kappa 0, and their ratio gamma rho/gamma kappa. For blood, liver, and skeletal muscle, the values derived at 6 MHz for d are approximately 5, 55, and 75 microns and for gamma rho/gamma kappa are 0.5, 0.15, and 0.28, respectively. These results are, in particular, at variance with the commonly made assumption, based on evidence from low-frequency measurements, that the ratio gamma rho/gamma kappa is sufficiently small that density terms can be ignored in calculations of human tissue scattering.

Acoustic Stimulation↗

PubMed2005

Population pharmacokinetics of delavirdine and N-delavirdine in HIV-infected individuals.

OBJECTIVE: Delavirdine is a non-nucleoside reverse transcriptase inhibitor used in combination regimens for the treatment of HIV-1 infection. Our objective was to characterise the population pharmacokinetics of delavirdine in HIV-infected patients who participated in the adult AIDS Clinical Trials Group (ACTG) 260 and 261 studies. METHODS: ACTG 261 was a randomised, double-blind study of delavirdine 400mg three times daily, in various combination regimens; ACTG 260 was a concentration-targeted monotherapy study. Two hundred and thirty-four patients, and 1254 and 1251 plasma concentrations for delavirdine and N-delavirdine, respectively, were available for population pharmacokinetic analysis. The pharmacokinetic model (and initial parameters), based on previous studies, included two compartments for delavirdine (peripheral and central) and parallel clearance pathways (nonlinear conversion to N-delavirdine and first order clearance from the body). The model was one compartment for N-delavirdine with first order clearance. Diurnal variation of delavirdine and N-delavirdine oral clearance was modelled as a cosine function, with amplitude variation a fitted parameter. Pharmacokinetic parameter estimates were derived from iterative two-stage analysis; observed delavirdine and N-delavirdine concentrations fit with weighting by the inverse observation variance. Covariates were analysed by multiple general linear modelling. RESULTS: The mean (percent coefficient of variation [%CV]) CD4 count was 315 (109) cells/mm(3), weight 76.9 (14.7) kg, age 37 (8.5) years, and 15% of the population were women. Mean (%CV) population pharmacokinetic parameter estimates for delavirdine were: volume of distribution at steady state 67.6 (100) L, intrinsic oral clearance 19.8 (64) L/h, concentration at half the maximum velocity of metabolism (V(max)) 6.3 (69) micromol/L and first order oral clearance 0.57 (86) L/h. For N-delavirdine, the mean (%CV) apparent volume of distribution was 24.7 (75) L and apparent clearance 29.7 (42) L/h. The mean V(max) was 1376 (68) mg/day. The final model for average intrinsic clearance of delavirdine included race, sex, weight and age as significant covariates (p < 0.05); however, these covariates do not explain a significant proportion of the overall variability in the population. CONCLUSIONS: Delavirdine disposition exhibits nonlinear pharmacokinetics and large interpatient variability, and is significantly altered by time of day (impacting potential therapeutic drug monitoring and future pharmacokinetic study designs). Although race and sex appear to influence delavirdine pharmacokinetics, men and women and patients of different races should receive similar mg/kg dosage regimens. The presence of large interpatient variability supports the further investigation of the utility of therapeutic drug monitoring for delavirdine, if target drug concentrations can be better defined.

Adolescent↗

PubMed1996

Two-stage designs for the logistic regression model in single-agent bioassays.

In this paper we focus on the use of a two-stage procedure for logistic regression that emphasizes predicting response through the use of the Q-optimality criterion. The use of D-optimality in the first stage is primarily to allow best possible parameter estimates as one enters the second stage. However, it is important to understand that there are many ways to formulate the two-stage procedure. It may involve any optimality criterion in either stage. In fact, theoretically, one need not stop at two stages. It was our intention in this paper to demonstrate the potential in the two-stage procedure in cases in which good initial parameter estimates are not available. Those investigators who are interested in the software for the two-stage procedure described here should contact Dr. William R. Myers.

Animals↗

PubMed1986

Analysis of the volume of red blood cells: application of the expectation-maximization algorithm to grouped data from the doubly-truncated lognormal distribution.

In accordance with general principles recommended by the International Committee for Standardization in Haematology (1982, Journal of Clinical Pathology 35, 1320-1322), we have developed statistical methods for the analysis of red cell volume distributions. To select an appropriate reference distribution for goodness-of-fit testing, we derived a mathematical model of erythropoiesis that predicted a lognormal form for the distribution of erythrocyte volumes. Model predictions were then tested using samples obtained from 50 healthy individuals. Each grouped red cell volume distribution was doubly-truncated to eliminate artifactual frequency counts. Distribution parameter estimates were computed using the expectation-maximization algorithm, a missing information technique. Results of the one-sample chi-square goodness-of-fit test showed a fairly even distribution of P-values over the interval. Examples of the application of these statistical procedures to distributions from patients with anemia are given. Our results suggest that, for the analysis of red blood cell volumes, (i) parameter estimation should be made with the expectation-maximization method, and (ii) the truncated lognormal distribution should be used as a reference distribution for goodness-of-fit testing. This method could be applied to any set of grouped doubly-truncated data which, after transformation, follows the normal model.

Anemia, Hypochromic↗

PubMed2000

Phylogenetic relationships among the phrynosomatid sand lizards inferred from mitochondrial DNA sequences generated by heterogeneous evolutionary processes.

Nucleotide sequences of the mitochondrial protein coding cytochrome b (cyt b; 650 bp) and small-subunit 12S ribosomal RNA (approximately 350 bp) genes were used in analyses of phylogenetic relationships among extant phrynosomatid sand lizards, including an examination of competing hypotheses regarding the evolution of "earlessness." Sequences were obtained from all currently recognized species of sand lizards as well as representatives of the first and second outgroups and analyzed using both parsimony and likelihood methods. The cyt b data offer strong support for relationships that correspond with relatively recent divergences and moderate to low support for relationships reflecting more ancient divergences within the clade. These data support monophyly of the "earless" taxa, the placement of Uma as the sister taxon to the other sand lizards, and monophyly of all four taxa traditionally ranked as genera. All well-supported relationships in the 12S phylogeny are completely congruent with well-supported relationships in the cyt b phylogeny; however, the 12S data alone provide very little support for deeper divergences. Phylogenetic relationships within species are concordant with geography and suggest patterns of phylogeographic differentiation, including the conclusion that at least one currently recognized species (Holbrookia maculata) actually consists of more than one species. By independently optimizing likelihood model parameters for various subsets of the data, we found that nucleotide substitution processes vary widely between genes and among the structural and functional regions or classes of sites within each gene. Therefore, we compared competing phylogenetic hypotheses, using parameter estimates specific to those subsets, analyzing the subsets separately and in various combinations. The hypothesis supported by the cyt b data was favored over rival hypotheses in all but one of the five comparisons made with the entire data set, including the set of partitions that best explained the data, although we were unable to confidently reject (P < 0.05) alternative hypotheses. Our results highlight the importance of optimizing models and parameter estimates for different genes or parts thereof--a strategy that takes advantages of the strengths of both combining and partitioning data.

Animals↗

PubMed2001

The use of multiple imputation for the analysis of missing data.

This article provides a comprehensive review of multiple imputation (MI), a technique for analyzing data sets with missing values. Formally, MI is the process of replacing each missing data point with a set of m > 1 plausible values to generate m complete data sets. These complete data sets are then analyzed by standard statistical software, and the results combined, to give parameter estimates and standard errors that take into account the uncertainty due to the missing data values. This article introduces the idea behind MI, discusses the advantages of MI over existing techniques for addressing missing data, describes how to do MI for real problems, reviews the software available to implement MI, and discusses the results of a simulation study aimed at finding out how assumptions regarding the imputation model affect the parameter estimates provided by MI.

Bias↗

PubMed1993

Improved frequency resolution in multidimensional constant-time experiments by multidimensional Bayesian analysis.

The resolution of spectral frequencies in NMR data obtained from discrete Fourier transformation (DFT) along D constant-time dimensions can be improved significantly through extrapolation of the D-dimensional free induction decay (FID) by multidimensional Bayesian analysis. Starting from Bayesian probability theory for parameter estimation and model detection of one-dimensional time-domain data [Bretthorst, (1990) J. Magn. Reson., 88, 533-551; 552-570; 571-595], a theory for the D-dimensional case has been developed and implemented in an algorithm called BAMBAM (BAyesian Model Building Algorithm in Multidimensions). BAMBAM finds the most probable sinusoidal model to account for the systematic portion of any D-dimensional stationary FID. According to the parameters estimated by the algorithm, the FID is extrapolated in D dimensions prior to apodization and Fourier transformation. Multidimensional Bayesian analysis allows for the detection of signals not resolved by the DFT alone or even by sequential one-dimensional extrapolation from mirror-image linear prediction prior to the DFT. The procedure has been tested with a theoretical two-dimensional dataset and with four-dimensional HN(CO)CAHA (Kay et al. (1992) J. Magn. Reson., 98, 443-450) data from a small protein (8 kDa) where BAMBAM was applied to the 13C alpha and H alpha constant-time dimensions.

Algorithms↗

PubMed1996

Pharmacodynamic analysis of sparse data from concentration- and effect-controlled clinical trials guided by a pilot study. An investigation by simulations.

The purpose of this investigation was to explore, by computer simulation, the utility of two different clinical trial designs with sparse sampling (three concentration--effect measurements per subject) for population pharmacodynamic studies when the targeted drug concentration or effect measurements are determined by application of optimal sampling theory based on the results of a preceding, data-intensive pilot study. The two design paradigms were concentration-controlled and pharmacologic effect-controlled randomized clinical trials, respectively. The drug concentration--pharmacologic effect relationship was assumed to be describable by the Hill (sigmoid Emax) equation without hysteresis. Intersubject variability was represented by coefficients of variation of 30, 40, and 30% for Emax, EC50, and gamma, respectively. Random controller imprecision and measurement errors were included. Concentration and effect data for 100 subjects were generated by Monte Carlo simulation (ADAPT II), and pharmacodynamic parameter values were obtained by iterative two-stage analysis. These were then used to predict effect intensities over a range of drug concentrations, and the results were compared with those obtained by use of the true parameter values. Concentration- and effect-controlled trial designs were simulated in two forms: unconstrained and constrained with respect to the highest allowed targeted drug concentration or effect intensity. It was found that both types of unconstrained trials yielded good and comparable parameter estimates whereas the constrained trials (which are clinically more realistic) yielded more biased and imprecise estimates of individual pharmacodynamic parameters. Nevertheless, use of the latter to determine the effect intensities produced by different drug concentrations yielded good estimates but only in the range covered by the targeted concentration or effect measurements. For concentration-controlled trials it appears essential that the individuals in the pilot group and the clinical study group be drawn from the same population. Effect-controlled trials gave good results even when the pilot group was not representative of the population (e.g., for an aberrant subpopulation).

Clinical Trials as Topic↗

PubMed2000

Cellular energetics analysis by a mathematical model of energy balance: estimation of parameters in human skeletal muscle.

Cellular energy balance requires that the physiological demands by ATP-utilizing functions be matched by ATP synthesis to sustain muscle activity. We devised a new method of analysis of these processes in data from single individuals. Our approach is based on the logic of current information on the major mechanisms involved in this energy balance and can quantify not directly measurable parameters that govern those mechanisms. We use a mathematical model that simulates by ordinary, nonlinear differential equations three components of cellular bioenergetics (cellular ATP flux, mitochondrial oxidative phosphorylation, and creatine kinase kinetics). We incorporate data under resting conditions, during the transition toward a steady state of stimulation and during the transition during recovery back to the original resting state. Making use of prior information about the kinetic parameters, we fitted the model to previously published dynamic phosphocreatine (PCr) and inorganic phosphate (P(i)) data obtained in normal subjects with an activity-recovery protocol using (31)P nuclear magnetic resonance spectroscopy. The experiment consisted of a baseline phase, an ischemic phase (during which muscle stimulation and PCr utilization occurred), and an aerobic recovery phase. The model described satisfactorily the kinetics of the changes in PCr and P(i) and allowed estimation of the maximal velocity of oxidative phosphorylation and of the net ATP flux in individuals both at rest and during stimulation. This work lays the foundation for a quantitative, model-based approach to the study of in vivo muscle energy balance in intact muscle systems, including human muscle.

Energy Metabolism↗

PubMed2006

Dimensional analysis of MINMOD leads to definition of the disposition index of glucose regulation and improved simulation algorithm.

BACKGROUND: Frequently Sampled Intravenous Glucose Tolerance Test (FSIVGTT) together with its mathematical model, the minimal model (MINMOD), have become important clinical tools to evaluate the metabolic control of glucose in humans. Dimensional analysis of the model is up to now not available. METHODS: A formal dimensional analysis of MINMOD was carried out and the degree of freedom of MINMOD was examined. Through re-expressing all state variable and parameters in terms of their reference scales, MINMOD was transformed into a dimensionless format. Previously defined physiological indices including insulin sensitivity, glucose effectiveness, and first and second phase insulin responses were re-examined in this new formulation. Further, the parameter estimation from FSIVGTT was implemented using both the dimensional and the dimensionless formulations of MINMOD, and the performances were compared utilizing Monte Carlo simulation as well as real human FSIVGTT data. RESULTS: The degree of freedom (DOF) of MINMOD was found to be 7. The model was maximally simplified in the dimensionless formulation that normalizes the variation in glucose and insulin during FSIVGTT. In the new formulation, the disposition index (Dl), a composite parameter known to be important in diabetes pathology, was naturally defined as one of the dimensionless parameters in the system. The numerical simulation using the dimensionless formulation led to a 1.5-5 fold gain in speed, and significantly improved accuracy and robustness in parameter estimation compared to the dimensional implementation. CONCLUSION: Dimensional analysis of MINMOD led to simplification of the model, direct identification of the important composite factors in the dynamics of glucose metabolic control, and better simulations algorithms.

Algorithms↗

PubMed1985

Comparison of several non-linear-regression methods for fitting the Michaelis-Menten equation.

The known jackknife methods (i.e. standard jackknife, weighted jackknife, linear jackknife and weighted linear jackknife) for the determination of the parameters (as well as of their confidence regions) were tested and compared with the simple Marquardt's technique (comprising the calculation of confidence intervals from the variance-co-variance matrix). The simulated data corresponding to the Michaelis-Menten equation with defined structure and magnitude of error of the dependent variable were used for fitting. There were no essential differences between the results of both point and interval parameter estimations by the tested methods. Marquardt's procedure yielded slightly better results than the jackknives for five scattered data points (the use of this method is advisable for routine analyses). The classical jackknife was slightly superior to the other methods for 20 data points (this method can be recommended for very precise calculations if great numbers of data are available). The weighting does not seem to be necessary in this type of equation because the parameter estimates obtained with all methods with the use of constant weights were comparable with those calculated with the weights corresponding exactly to the real error structure whereas the relative weighting led to rather worse results.

Enzymes↗

PubMed1984

The detection of major loci by segregation and linkage analysis: a simulation study.

Simulated multigenerational pedigrees were analyzed using the program GENPED and POINTER to examine the 1) limits of segregation analysis for detecting single locus, two-allele transmission of a dichotomous trait and 2) accuracy of the parameter estimates. Ten data sets of 30 pedigrees each (approximately 25 persons per pedigree) were simulated. The genotypic penetrance values were varied but the population prevalence of the trait was kept constant at 2%. For some data sets a linked marker locus was also simulated. Previous results had shown that a single major locus could be easily detected when the heterozygote penetrance (f1) was high or midway between the two homozygote penetrances. In this study, we found a single major locus could not be consistently detected by either method of segregation analysis when f1 was "low" to "intermediate." Accuracy of the parameter estimates depended on assumptions about the population prevalence. In those cases where the major locus could not be detected by segregation analysis, linkage to a marker locus could be detected as long as the marker was closely linked and there were not phenocopies in the population. Owing to the limited number of simulations in this study, we cannot generalize these findings. However, they provide a basis for further testing of methods of segregation analysis when factors such as the parameter values, family structure, and ascertainment scheme are varied.

Biometry↗

PubMed2006

Myocardial material parameter estimation-a comparative study for simple shear.

The study of ventricular mechanics-analyzing the distribution of strain and stress in myocardium throughout the cardiac cycle-is crucially dependent on the accuracy of the constitutive law chosen to represent the highly nonlinear and anisotropic properties of passive cardiac muscle. A number of such laws have been proposed and fitted to experimental measurements of stress-strain behavior. Here we examine five of these laws and compare them on the basis of (i) "goodness of fit:" How well they fit a set of six shear deformation tests, (ii) "determinability:" How well determined the objective function is at the optimal parameter fit, and (iii) "variability:" How well determined the material parameters are over the range of experiments. These criteria are utilized to discuss the advantages and disadvantages of the constitutive laws.

Animals↗

PubMed2003

Population pharmacokinetic analysis of nonlinear behavior of piperacillin during intermittent or continuous infusion in patients with cystic fibrosis.

The purpose of this study was to describe the nonlinear pharmacokinetics of piperacillin observed during intermittent infusion and continuous infusion by using a nonparametric population modeling approach. Data were 120 serum piperacillin concentration measurements from eight adult cystic fibrosis (CF) patients. Individual pharmacokinetic parameter estimates during intermittent infusion or continuous infusion were calculated by noncompartmental analysis and with a maximum iterative two-stage Bayesian estimator. To simultaneously describe concentration-time data during intermittent infusion and continuous infusion, nonlinear models were parameterized as two-compartment Michaelis-Menten models. Models were fit to the data with the nonparametric expectation maximization algorithm. The calculations were executed on a remote supercomputer. Nonlinear models were evaluated by log-likelihood estimates, residual plots, and R(2) values, and predictive performance was based on bias (mean weighted error [MWE]) and precision (mean weighted square error [MWSE]). A linear pharmacokinetic model could not describe combined intermittent infusion and continuous infusion data well. A good population model fit to the intermittent infusion and continuous infusion data was obtained with the constructed nonlinear models. Maximum a posteriori probability (MAP) Bayesian R(2) values for the nonlinear models were 0.96 to 0.97. Median parameter estimates for the best nonlinear model were as follows: K(m), 58 +/- 75 mg/liter (mean and standard deviation); V(max), 1,904 +/- 1,009 mg/h; volume of distribution of the central compartment, 14.1 +/- 3.0 liters; k(12), 0.63 +/- 0.41 h(-1); and k(21), 0.37 +/- 0.19 h(-1). The median bias (MWE) and precision (MWSE) values for MAP Bayesian estimation with the Michaelis-Menten model were 0.05 and 4.6 mg/liters, respectively. The developed nonlinear pharmacokinetic models can be used to optimize piperacillin therapy administered via continuous infusion in patients with CF and have distinct advantages over conventional linear models.

Adult↗

PubMed2004

Properties of case/pseudocontrol analysis for genetic association studies: Effects of recombination, ascertainment, and multiple affected offspring.

The case/pseudocontrol approach is a general framework for family-based association analysis, incorporating several previously proposed methods such as the transmission/disequilibrium test and log-linear modelling of parent-of-origin effects. In this report, I examine the properties of methods based on a case/pseudocontrol approach when applied to a linked marker rather than (or in addition to) the true disease locus or loci, and when applied to sibships that have been ascertained on, or that may simply contain, multiple affected sibs. Through simulations and analytical calculations, I show that the expected values of the observed relative risk parameters (estimating quantities such as effects due to a child's own genotype, maternal genotype, and parent-of-origin) depend crucially on the ascertainment scheme used, as well as on whether there is non-negligible recombination between the true disease locus and the locus under study. In the presence of either recombination or ascertainment on multiple affected offspring, methods based on conditioning on parental genotypes are shown to give unbiased genotype relative risk estimates at the true disease locus (or loci) but biased estimates of population genotype relative risks at a linked marker, suggesting that the resulting estimates may be misleading when used to predict the power of future studies. Methods that allow for exchangeability of parental genotypes are shown (in the presence of either recombination or ascertainment on multiple affected offspring) to produce false-positive evidence of maternal genotype effects when there are true parent-of-origin or mother-child interaction effects, even when analyzing the true locus. These results suggest that care should be taken in both the interpretation and application of parameter estimates obtained from family-based genetic association studies.

Algorithms↗

PubMed2001

Bayesian restoration of ion channel records using hidden Markov models.

Hidden Markov models have been used to restore recorded signals of single ion channels buried in background noise. Parameter estimation and signal restoration are usually carried out through likelihood maximization by using variants of the Baum-Welch forward-backward procedures. This paper presents an alternative approach for dealing with this inferential task. The inferences are made by using a combination of the framework provided by Bayesian statistics and numerical methods based on Markov chain Monte Carlo stochastic simulation. The reliability of this approach is tested by using synthetic signals of known characteristics. The expectations of the model parameters estimated here are close to those calculated using the Baum-Welch algorithm, but the present methods also yield estimates of their errors. Comparisons of the results of the Bayesian Markov Chain Monte Carlo approach with those obtained by filtering and thresholding demonstrate clearly the superiority of the new methods.

Bayes Theorem↗

PubMed2003

Comparative pharmacokinetic analysis by standard two-stage method versus nonparametric population modeling.

STUDY OBJECTIVE: To compare the two-stage method, a widely used analytical method in pharmacokinetic studies, with nonparametric population modeling by using the same data set for determining the oral bioavailability of ribavirin. DESIGN: Pharmacokinetic analysis. Clinical research center. MATERIAL: Oral bioavailability data of ribavirin determined previously in six healthy adults. INTERVENTION: After 13C3-ribavirin 150 mg intravenously and unlabeled ribavirin 400 mg orally had been given 1 hour apart, serial serum and urine samples were obtained for up to 169 hours. Concentrations of 13C3-ribavirin and unlabeled ribavirin in serum and urine were determined by a high-performance liquid chromatography tandem mass spectrometric method. MEASUREMENTS AND MAIN RESULTS: Serum and urine concentration-time profiles were comodeled with a three-compartment model. The analysis was performed again by using the nonparametric population analysis technique. Serum ribavirin concentrations underwent Monte Carlo simulation for 1000 subjects receiving a single 600-mg oral dose. Both methods were similar in determining the mean +/- SD bioavailability (51.8 +/- 21.8% by the two-stage method vs 54.8 +/- 16.4% by nonparametric modeling, p=0.79). However, the estimates of dispersion of model parameters and simulated drug exposures were substantially reduced by the population-modeling technique, as it takes into account covariance among model parameters and intersubject variability. CONCLUSION: Although the study sample was small, our parallel analyses of the same data set clearly demonstrated that more precise parameter estimates are likely to result with the population-modeling technique. Having accurate and precise estimation of population pharmacokinetic parameters and their true variances is crucial, as, at any dose, there'will be a lower probability of encountering a concentration-driven toxicity because of fewer outliers as the variance associated with the parameters decreases.

Adult↗