similar to: Pharmacokinetic and pharmacodynamic modeling and simulation

Analysis of Repeated Measurements By Dr. Ronald Geskus April 27, 2007 Amsterdam, The Netherlands http://www.can.nl/events/details.php?id=31 This course is aimed at everyone who is working with data that contain repeated measurements on persons or otherwise related data and who wants to analyse such data in a proper way. In many situations one may have data that show some

________________________________ 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 List, I have a problem with auth for just one user: dovecot: Sep 30 09:56:16 Info: auth(default): new auth connection: pid=3809 dovecot: Sep 30 09:56:17 Info: auth(default): client in: AUTH 1 PLAIN service=IMAP secured lip=127.0.0.1 rip=127.0.0.1 resp=AGoucnVpc0BtZXJreC12ZXJrZXJrLm5sAGJsb2VtMDEh dovecot: Sep 30 09:56:17 Info: auth(default): pam(j.ruis at

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

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

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

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

Dear R-help subscribers, I have a quite stupid question about using lapply. I have the following function: create.gradient <- function(i){ colorgrad01<-color.scale(seq(0,1,by=0.01), extremes=c("red","blue")) tree1$edge[i,1] -> x tree1$edge[i,2] -> y print(x) print(y) all2[x] -> z all2[y] -> z2 round(z, digits = 2) -> z round(z2, digits = 2) -> z2

Dear R-help subscribers; I have a question regarding making gradients in R. I've searched on the web, but was only able to find functions that make a gradient between color X and Y, which is not what I want. I want to 'pick out' individual, smaller pieces of a gradient based on a range of numbers. Say that I have a range of numbers, leading from 0 to 1. Then I want 0 to refer to

Dear people from the R help list, I have a question that I can't get my head around to start answering, that is why I am writing to the list. I have data in a format like this (tabs might look weird): John A1 1 0 1 John A2 1 1 1 John A3 1 0 0 Mary A1 1 0 1 Mary A2 0 0 1 Mary A3 1 1 0 Peter A1 1

Hi, I just wonder if R is still used for PK analysis. However, I have to use R for some purposes anyways. Here is a really strange problem I am running into and I hope to get some assistance from the group. The following code works fine in S-Plus (Population estimates and MAP estimates look reasonable ). cs.fit<-nlme ( CONC~phenoModel(CID,TIME, DOSE, lCl, lV), fixed = lCl+lV ~1,

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

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

Dear all, We are looking for bright and motivated candidates to join our pharmacometric modelling team at the University of Cape Town. Pharmacometrics is an emerging 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

Hi all, When I try to make a connection to our windows server with smbclient: smbclient //server/dira/dirb/dirc -U username -W workgroup Password: ***** I get a working ftp-like connection to our data. When I try to make the same connection with mount.cifs: mount.cifs //server/dira/dirb/dirc /mnt/mnt_dir -o user=877790 dom=workgroup Password: ***** I get a mount to a location which appears

All, I am constructing a pharmacokinetic dataset and have hit a snag. The dataset can be demonstrated in the following way: myData <- data.frame( evid = c(1, 0, 0, 0, 1, 0, 1, 1, 1, 0), time = 1:10, last.dose.time = c(1, 1, 1, 1, 5, 5, 7, 8, 9, 9) ) The evid field is an indicator variable for whether the associated observation is a dosing record (when it takes value 1) or an

All, I have been able to successfully use the optim( ) function with "L-BFGS-B" to find reasonable parameters for a one-compartment open pharmacokinetic model. My loss function in this case was squared error, and I made no assumptions about the distribution of the plasma values. The model appeared to fit pretty well. Out of curiosity, I decided to try to use nlminb( ) applied to a