search for: pharmacodynamics

Pharmacokinetic and pharmacodynamic modeling and simulation By Dr. Jan Freijer September 24, 2009 Amsterdam, The Netherlands http://www.can.nl/events/details.php?id=57 This course is aimed at users of R or S-PLUS in the bio-pharmaceutical sciences who would like to use R for clinical trial simulations. topics include Working with packages in R - MASS -

Dear R-users, I am pleased to announce the release of scaRabee, a new R package which constitutes a toolkit for modeling and simulation in the field of pharmacometrics. It was designed as a user-friendly interface to create and modify model scripts, define system observations and inputs, and run simulation or estimation analysis. scaRabee provides templates for the definition of

saemix implements the SAEM (stochastic approximation EM) algorithm for parameter estimation in non-linear mixed effect models, used to model longitudinal data. Longitudinal data are particularly prominent in pharmacokinetics (study of drug concentrations versus time) and pharmacodynamics (study of drug effect versus time), but the SAEM algorithm has also been successfully applied in many other areas and we would like to encourage you to try saemix. More details can be found in the user guide included in the package, which encloses a section showing different examples using SAE...

Dr. Andrzej Galecki will present his online course "Mixed Effects Models with Applications" May 12 ? June 9 at statistics.com. This course will explain the basic theory of linear and non-linear mixed effects models, including hierarchical linear models (HLM). It will outline the algorithms used for estimation, primarily for models involving normally distributed errors, and will provide

saemix implements the SAEM (stochastic approximation EM) algorithm for parameter estimation in non-linear mixed effect models, used to model longitudinal data. Longitudinal data are particularly prominent in pharmacokinetics (study of drug concentrations versus time) and pharmacodynamics (study of drug effect versus time), but the SAEM algorithm has also been successfully applied in many other areas and we would like to encourage you to try saemix. More details can be found in the user guide included in the package, which encloses a section showing different examples using SAE...

Dear R-users, I am pleased to announce the release of scaRabee, a new R package which constitutes a toolkit for modeling and simulation in the field of pharmacometrics. It was designed as a user-friendly interface to create and modify model scripts, define system observations and inputs, and run simulation or estimation analysis. scaRabee provides templates for the definition of

...ging discipline that uses mathematical and statistical tools to quantify drug, disease, and trial information to aid efficient drug development and/or regulatory decisions. It designs and applies mathematical models to describe the relationship between drug exposure (pharmacokinetics) and response (pharmacodynamics) for both desired and undesired effects, and aims to include in such models the effects of individual patient characteristics. Our pharmacometrics group has established PK/PD modelling expertise in the disease area of tuberculosis, HIV, and malaria. It is active internationally and enjoys on-going...

Dear all, at the Division of Clinical Pharmacology at the University of Cape Town (South Africa) we are looking for highly motivated science/engineering PhD graduates to join our pharmacometrics group as a post-doctoral fellow. Pharmacometrics is an emerging discipline that applies mathematical modelling and simulation to pharmacology, aiding the interpretation of data from clinical trials,

TOP Institute Pharma (TI Pharma) has granted our proposal to set up a mechanism-based PKPD modelling platform. This platform focuses on the transfer of knowledge from academia to the pharmaceutical industry and is a collaborative effort of four excellent academic institutes and six leading global pharmaceutical industries. Unique to this platform is the availability of shared databases on

Two Postdoctoral fellows (fulltime) Leiden University, Leiden, The Netherlands Job description ________________________________________ TOP Institute Pharma (TI Pharma) has granted our proposal to set up a mechanism-based PK-PD modelling platform. This platform focuses on the transfer of knowledge from academia to the pharmaceutical industry and is a collaborative effort of

________________________________ Principal Post-Doctoral Fellow PKPD modelling platform (full time) Leiden University, Leiden, The Netherlands <javascript:doredirect();> Job description ________________________________ TOP Institute Pharma (TI Pharma) has granted our proposal to set up a mechanism-based PK-PD modelling platform. This platform focuses on the transfer of

Post-Doctoral Fellowship Modelling of Cardiovascular Safety (full time) Leiden University, Leiden, The Netherlands <javascript:doredirect();> Job description TOP Institute Pharma (TI Pharma) has granted our proposal to set up a mechanism-based PKPD modelling platform. This platform focuses on the transfer of knowledge from academia to the pharmaceutical industry and is a

Hi there, it might be a very simple question and I'd be glad to even get a link to some useful documentation... I have several data sets, I'd like to fit to a gaussian distribution. I've tried to give an estimate of the mean and the sd of this distribution but still, I run into problems if these estimates are not close enough. For example, nls() breaks with this message: singular

CRAN (and crantastic) updates this week New packages ------------ * allan (1.0) Alan Lee http://crantastic.org/packages/allan Automates Large Linear Analysis Model Fitting * andrews (1.0) Jaroslav Myslivec http://crantastic.org/packages/andrews Andrews curves for visualization of multidimensional data * anesrake (0.3) Josh Pasek http://crantastic.org/packages/anesrake This