RESUMEN
The lipid modifications which occur on Bombyx mori Ras proteins BmRas1, BmRas2 and BmRas3 were studied by metabolic labelling in an insect cell-free protein synthesis system and in a baculovirus expression system, using specific inhibitors of protein prenylation and protein palmitoylation. In addition, the subcellular localization of BmRas proteins was examined using EGFP fusion proteins of constitutively active forms of BmRas proteins transiently expressed in Sf9 cells. As a result, it was revealed that the three B. mori Ras proteins BmRas1, BmRas2 and BmRas3 are neither farnesylated nor palmitoylated but are geranylgeranylated for localization to the plasma membrane of insect cells. Thus, the mechanism of membrane binding of insect Ras proteins is quite different from that reported for mammalian Ras proteins.
Asunto(s)
Bombyx/metabolismo , Proteínas de Insectos/metabolismo , Lipoilación , Prenilación , Proteínas ras/metabolismo , Secuencia de Aminoácidos , Animales , Baculoviridae/genética , Bombyx/citología , Línea Celular , Membrana Celular/metabolismo , Sistema Libre de Células , Evolución Molecular , Vectores Genéticos/genética , Humanos , Proteínas de Insectos/química , Proteínas de Insectos/genética , Datos de Secuencia Molecular , Biosíntesis de Proteínas , Transporte de Proteínas , Coloración y Etiquetado , Proteínas ras/química , Proteínas ras/genéticaRESUMEN
Biomedical researchers usually test the null hypothesis that there is no difference of the population mean of pharmacokinetics (PK) parameters between genotypes by the Kruskal-Wallis test. Although a monotone increasing pattern with a number of alleles is expected for PK-related genes, the Kruskal-Wallis test does not consider a monotonic response pattern. For detecting such patterns in clinical and toxicological trials, a maximum contrast method has been proposed. We show how that method can be used with pharmacogenomics data to a develop test of association. Further, using simulation studies, we compare the power of the modified maximum contrast method to those of the maximum contrast method and the Kruskal-Wallis test. On the basis of the results of those studies, we suggest rules of thumb for which statistics to use in a given situation. An application of all three methods to an actual genome-wide pharmacogenomics study illustrates the practical relevance of our discussion.
Asunto(s)
Estudio de Asociación del Genoma Completo/estadística & datos numéricos , Modelos Genéticos , Modelos Estadísticos , Farmacogenética/estadística & datos numéricos , Farmacocinética , Polimorfismo de Nucleótido Simple , Simulación por Computador , Genotipo , Humanos , Método de Montecarlo , FenotipoRESUMEN
In clinical phase I trials, pharmacokinetic sampling schedules often have to be modified while the trials proceed. The modifications are based on the observations from a limited number of subjects or only one subject in extreme cases. This paper describes a Kullback-Leibler information approach for modifying pharmacokinetic sampling schedules in clinical phase I trials. The proposed approach presupposes that the pharmacokinetic profile for each subject is specified by an appropriate pharmacokinetic model and the subject-specific parameters. The best modification plan is selected from arbitrarily chosen candidates based on the Kullback-Leibler information. Applications are given to a simulation study and an actual phase I trial of an anti-cancer drug.
Asunto(s)
Ensayos Clínicos Fase I como Asunto/estadística & datos numéricos , Monitoreo de Drogas/estadística & datos numéricos , Farmacocinética , Intervalos de Confianza , Humanos , Cómputos Matemáticos , Modelos EstadísticosRESUMEN
We conducted a population pharmacokinetic analysis of ephedrine, the main effective constituent of the two Kampo prescriptions, Sho-seiryu-to (Xiao-Qing-Long-Tang, Formula divinitatis caeruleae minor) and Kakkon-to (Ge-Gen-Tang, Formula puerariae), which are routinely used in the treatment of allergic rhinitis. Major pharmacokinetic differences were found in AUC(0-infinity), Cmax and the averages of the distribution volume between the two prescriptions. Using the pharmacokinetic results, we also conducted a simulation-based study comparing the pharmacokinetic profiles of ephedrine for the usual dosage regimen, a constant dose D three times a day before meals, and two alternative dosage regimens which are often used when patients' symptoms are not improved in the morning using the usual dosage regimen. The results suggested that one of the two alternative dosage regimens, two times D before breakfast and D in the afternoon, was the most effective from the pharmacokinetic viewpoint. This result was in accordance with our clinical experience.
Asunto(s)
Antialérgicos/farmacocinética , Efedrina/farmacocinética , Medicina Kampo , Adulto , Algoritmos , Antialérgicos/administración & dosificación , Antialérgicos/uso terapéutico , Área Bajo la Curva , Simulación por Computador , Prescripciones de Medicamentos , Efedrina/administración & dosificación , Efedrina/uso terapéutico , Humanos , Masculino , Población , Rinitis Alérgica Estacional/tratamiento farmacológicoRESUMEN
In population pharmacokinetic studies, one of the main objectives is to estimate population pharmacokinetic parameters specifying the population distributions of pharmacokinetic parameters. Confidence intervals for population pharmacokinetic parameters are generally estimated by assuming the asymptotic normality, which is a large-sample property, that is, a property which holds for the cases where sample sizes are large enough. In actual clinical trials, however, sample sizes are limited and not so large in general. Likelihood functions in population pharmacokinetic modelling include a multiple integral and are quite complicated. We hence suspect that the sample sizes of actual trials are often not large enough for assuming the asymptotic normality and that the asymptotic confidence intervals underestimate the uncertainties of the estimates of population pharmacokinetic parameters. As an alternative to the asymptotic normality approach, we can employ a bootstrap approach. This paper proposes a bootstrap standard error approach for constructing confidence intervals for population pharmacokinetic parameters. Comparisons between the asymptotic and bootstrap confidence intervals are made through applications to a simulated data set and an actual phase I trial.
Asunto(s)
Intervalos de Confianza , Farmacocinética , Adulto , Ensayos Clínicos Fase I como Asunto/métodos , Ensayos Clínicos Fase I como Asunto/estadística & datos numéricos , Interpretación Estadística de Datos , Demografía , Humanos , Infusiones Intravenosas/estadística & datos numéricos , Funciones de Verosimilitud , Masculino , Modelos Estadísticos , Método de Montecarlo , Valores de ReferenciaRESUMEN
For population pharmacokinetics in phase I trials, the standard two-stage (STS) method is quite appealing, especially to non-statisticians, because the method is theoretically and computationally simple. The method, however, does not take into account the uncertainty in estimating individual-specific parameters and gives biased estimates for population variances of pharmacokinetic parameters. This is one of the main reasons why the STS method is not generally recommended. This paper proposes a simple bootstrap modification of the STS method for estimating confidence intervals of population means and standard deviations of pharmacokinetic parameters in phase I trials. The proposed approach adopts a bootstrap bias correction in estimating population variances of pharmacokinetic parameters. Applications are given to a simulated data set and an actual phase I trial to show how the proposed approach works in practice.
Asunto(s)
Ensayos Clínicos Fase I como Asunto/estadística & datos numéricos , Intervalos de Confianza , Farmacocinética , Ensayos Clínicos Fase I como Asunto/métodos , Interpretación Estadística de Datos , Demografía , Humanos , Modelos EstadísticosRESUMEN
This paper describes a use of Monte Carlo integration for population pharmacokinetics with multivariate population distribution. In the proposed approach, a multivariate lognormal distribution is assumed for a population distribution of pharmacokinetic (PK) parameters. The maximum likelihood method is employed to estimate the population means, variances, and correlation coefficients of the multivariate lognormal distribution. Instead of a first-order Taylor series approximation to a nonlinear PK model, the proposed approach employs a Monte Carlo integration for the multiple integral in maximizing the log likelihood function. Observations below the lower limit of detection, which are usually included in Phase 1 PK data, are also incorporated into the analysis. Applications are given to a simulated data set and an actual Phase 1 trial to show how the proposed approach works in practice.