Global ETD Search

41	Limited sampling strategies for estimation of cyclosporine exposure in pediatric hematopoietic stem cell transplant recipients : methodological improvement and introduction of sampling time deviation analysis Sarem, Sarem 12 1900 (has links) No description available. Pharmacokinetics Pharmacometrics Therapeutic Drug Monitoring Population-pharmacokinetics Pop-PK Limited Sampling Strategies Area Under the Curve Sampling Time Deviation Bayesian approach Cyclosporine Pharmacocinétique Pharmacométrie Suivi Thérapeutique Surface Sous la Courbe Écart de Temps d’Échantillonnage Pédiatrie Agents Immunosuppresseurs
42	Individualization of fixed-dose combination regimens : Methodology and application to pediatric tuberculosis / Individualisering av design och dosering av kombinationstabletter : Metodologi och applicering inom pediatrisk tuberkulos Yngman, Gunnar January 2015 (has links) Introduction: No Fixed-Dose Combination (FDC) formulations currently exist for pediatric tuberculosis (TB) treatment. Earlier work implemented, in the software NONMEM, a rational method for optimizing design and individualization of pediatric anti-TB FDC formulations based on patient body weight, but issues with parameter estimation, dosage strata heterogeneity and representative pharmacokinetics remained. Aim: To further develop the rational model-based methodology aiding the selection of appropriate FDC formulation designs and dosage regimens, in pediatric TB treatment. Materials and Methods: Optimization of the method with respect to the estimation of body weight breakpoints was sought. Heterogeneity of dosage groups with respect to treatment efficiency was sought to be improved. Recently published pediatric pharmacokinetic parameters were implemented and the model translated to MATLAB, where also the performance was evaluated by stochastic estimation and graphical visualization. Results: A logistic function was found better suited as an approximation of breakpoints. None of the estimation methods implemented in NONMEM were more suitable than the originally used FO method. Homogenization of dosage group treatment efficiency could not be solved. MATLAB translation was successful but required stochastic estimations and highlighted high densities of local minima. Representative pharmacokinetics were successfully implemented. Conclusions: NONMEM was found suboptimal for the task due to problems with discontinuities and heterogeneity, but a stepwise method with representative pharmacokinetics were successfully implemented. MATLAB showed more promise in the search for a method also addressing the heterogeneity issue. pharmacometrics pharmacokinetics PK population pharmacokinetics optimal design FDC fixed-dose combination pediatrics tuberculosis rifampicin pyrazinamide isoniazid ethambutol modeling simulation estimation allometric scaling stochastical simulation and estimation NONMEM MATLAB FO FOCE Expectation-Maximization algorithm importance sampling Nelder-Mead method logistic function discontinuity euclidean distance Sammon mapping global minimum local minima Pharmaceutical Sciences Farmaceutiska vetenskaper Bioinformatics (Computational Biology) Bioinformatik (beräkningsbiologi)
43	Tramadol in the elderly : pharmacokinetic and pharmacodynamic modelling in healthy young and elderly subjects Skinner-Robertson, Sybil 01 1900 (has links) No description available. Tramadol O-desmethyltramadol enantiomer non-compartmental analysis population pharmacokinetics population pharmacodynamics PK/PD pain tolerance threshold elderly geriatric pain Énantiomère Analyse non compartimentale Analyse populationnel pharmacocinétique Seuil de tolérance de douleur Personnes âgées Gériatrique Douleur
44	Comparison of Multiple Models for Diabetes Using Model Averaging Al-Mashat, Alex January 2021 (has links) Pharmacometrics is widely used in drug development. Models are developed to describe pharmacological measurements with data gathered from a clinical trial. The information can then be applied to, for instance, safely establish dose-response relationships of a substance. Glycated hemoglobin (HbA1c) is a common biomarker used by models within antihyperglycemic drug development, as it reflects the average plasma glucose level over the previous 8-12 weeks. There are five different nonlinear mixed-effects models that describes HbA1c-formation. They use different biomarkers such as mean plasma glucose (MPG), fasting plasma glucose (FPG), fasting plasma insulin (FPI) or a combination of those. The aim of this study was to compare their performances on a population and an individual level using model averaging (MA) and to explore if reduced trial durations and different treatment could affect the outcome. Multiple weighting methods were applied to the MA workflow, such as the Akaike information criterion (AIC), cross-validation (CV) and a bootstrap model averaging method. Results show that in general, models that use MPG to describe HbA1c-formation on a population level could potentially outperform models using other biomarkers, however, models have shown similar performance on individual level. Further studies on the relationship between biomarkers and model performances must be conducted, since it could potentially lay the ground for better individual HbA1c-predictions. It can then be applied in antihyperglycemic drug development and to possibly reduce sample sizes in a clinical trial. With this project, we have illustrated how to perform MA on the aforementioned models, using different biomarkers as well as the difference between model weights on a population and individual level. pharmacometrics population pharmacokinetics pop-pk pop-PK diabetes model averaging MA cross-validation cv CV akaike information criterion Akaike aic AIC MPG mpg FPG fpg FPI fpi HbA1c hba1c farmakometri populationsfarmakokinetik diabetes model averaging MA cross-validation cv CV akaike Akaike aic AIC MPG mpg FPG fpg FPI fpi HbA1c hba1c Pharmaceutical Sciences Farmaceutiska vetenskaper

Page generated in 0.1392 seconds