Henrik Aalborg Nielsen

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The objective of the present analysis was to explore the use of stochastic differential equations (SDEs) in population pharmacokinetic/pharmacodynamic (PK/PD) modeling. The intra-individual variability in nonlinear mixed-effects models based on SDEs is decomposed into two types of noise: a measurement and a system noise term. The measurement noise(More)
The standard software for non-linear mixed-effect analysis of pharmacokinetic/pharmacodynamic (PK/PD) data is NONMEM while the non-linear mixed-effects package NLME is an alternative as long as the models are fairly simple. We present the nlmeODE package which combines the ordinary differential equation (ODE) solver package odesolve and the non-linear mixed(More)
AIMS To develop a population pharmacokinetic/pharmacodynamic (PK/PD) model of the hypothalamic-pituitary-gonadal (HPG) axis describing the changes in luteinizing hormone (LH) and testosterone concentrations following treatment with the gonadotropin-releasing hormone (GnRH) agonist triptorelin and the GnRH receptor blocker degarelix. METHODS Fifty-eight(More)
Acknowledgements First of all the authors wish to thank the Danish Energy Agency for financial support of this project under contract 1323/98-0025, Danish Energy Research Program. We also wish toA. for fruitful discussions during the startup phase of the project. i ii Summary Methods for on-line prediction of heat consumption in district heating systems(More)
Purpose. The objective of this study is to develop a population pharmacokinetic (PK) model that describes the subcutaneous (SC) depot formation of gonadotropin-releasing hormone (GnRH) antagonist degarelix, which is being developed for treatment of prostate cancer, exhibiting dose-volume and dose-concentration dependent absorption. Methods. The PK analysis(More)
In this paper, the two non-linear mixed-effects programs NONMEM and NLME were compared for their use in population pharmacokinetic/pharmacodynamic (PK/PD) modelling. We have described the first-order conditional estimation (FOCE) method as implemented in NONMEM and the alternating algorithm in NLME proposed by Lindstrom and Bates. The two programs were(More)
An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method and an updating procedure are combined into a new algorithm(More)
Short-term forecasting of wind generation requires a model of the function for the conversion of meteorological variables (mainly wind speed) to power production. Such a power curve is nonlinear and bounded, in addition to being nonstationary. Local linear regression is an appealing nonparametric approach for power curve estimation, for which the model(More)
The conditional parametric model is an extension of the well known linear regression model, obtained by replacing the parameters by smooth functions. Estimation in such models may be accomplished by fitting a, possibly larger, linear model locally to some explanatory variable(s). In this report the conditional parametric model is described together with a(More)
We present the results from an on-going project financed by the Danish PSO-fund where a number of subjects relevant for further automation and improvement of short term wind power forecasts methods are studied. The technological basis of the project is adaptive forecast methods as the methods forming the basis of WPPT (Wind Power Prediction Tool) – a well(More)