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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Optimal design for dose-exposure-response clinical
trials analyzed by nonlinear mixed effect models
- Mentr\, F (Paris)
DTSTART;TZID=Europe/London:20110810T114500
DTEND;TZID=Europe/London:20110810T123000
UID:TALK32301AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/32301
DESCRIPTION:Background: Nonlinear mixed effects models (NLMEM)
are increasingly used for analysis of dose-exposu
re-response models. Methods for population designs
evaluation/ optimisation are needed for complex m
odels to limit the number of samples in each patie
nt. Approaches for population designs optimisation
based on the Fisher information matrix for NLMEM
are developed\, using mostly first order approxima
tion of the model. Antiretroviral treatment in pat
ients with HIV infection is complex and show large
inter -individual variability. Pharmacokinetic an
d viral dynamic models are available to describe e
volution of concentrations\, viral loads and CD4 c
ounts. Parameters of these models are estimated th
rough NLMEM. \n\nObjectives: 1) to evaluate and op
timise designs in patients for the pharmacokinetic
study of an antiretroviral drug (zidovudine) and
its active metabolite using cost functions\, 2) to
evaluate and optimise designs for viral dynamic r
esponse and study power to compare treatments effi
cacy. \n\nMethods: We used the models and estimate
d parameters from data of patients of the COPHAR 2
- ANRS 111 trial. Measuring active metabolite con
centration of zidovudine is costly\, as they are i
ntracellular\, and we explored D-optimal populatio
n designs using various cost functions. The viral
dynamic model is a complex model written in ordina
ry differential equations. We proposed sparse desi
gns with limited number of visits per patient duri
ng the one year follow up. We studied the predicte
d power to compare two treatments. These analyses
were performed using PFIM3.2\, an R function that
we developed for population designs. \n\nResults:
We found a design with only three samples for zido
vudine and two samples for its active metabolite a
nd showed that optimal designs varied with cost fu
nctions. For the viral dynamic model\, we showed t
hat a design with 6 visits\, if optimally located\
, can provide good information on response. We eva
luated the power to compare two treatments and com
puted the number of subject needed to get adequate
power. \n\nConclusion: We showed that population
design optimisation provides efficient designs res
pecting clinical constraints in multi responses no
nlinear mixed effects models. \n
LOCATION:Seminar Room 1\, Newton Institute
CONTACT:Mustapha Amrani
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