XPOP - 2019 - Annual activity report

XPOP

XPOP - 2019

Project-Team Xpop

Team, Visitors, External Collaborators

Overall Objectives

Developing sound, useful and usable methods
Combining numerical, statistical and stochastic components of a model
Developing future standards

Research Program

Scientific positioning
The mixed-effects models
Computational Statistical Methods
Markov Chain Monte Carlo algorithms
Parameter estimation
Model building
Model evaluation
Missing data

Application Domains

Surface Enhanced Raman Spectroscopy
Management of severe trauma
Precision medicine and pharmacogenomics
Oncology
Anesthesiology
Intracellular processes
Population pharmacometrics
Mass spectrometry

Highlights of the Year

New Software and Platforms

mlxR
Rsmlx
SPIX

New Results

Modelling inheritance and variability of kinetic gene expression parameters in microbial cells
Main effects and interactions in mixed and incomplete data frames
Quantification of gemcitabine intravenous drugs
Low-rank model with covariates for count data analysis
Imputation and low-rank estimation with Missing Non At Random data
A mathematical model to predict BNP levels in hemodialysis patients
Analysis of the global convergence of (fast) incremental EM methods
Efficient Metropolis-Hastings sampling for nonlinear mixed effects models

Bilateral Contracts and Grants with Industry

Bilateral Contracts with Industry

Partnerships and Cooperations

National Initiatives
International Initiatives
International Research Visitors

Dissemination

Promoting Scientific Activities
Teaching - Supervision - Juries
Popularization

Bibliography

Publications of the year

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Section: New Results

A mathematical model to predict BNP levels in hemodialysis patients

Clinical interpretation of B-Type Natriuretic Peptide (BNP) levels in hemodialysis patients (HD) for fluid management remains elusive. We conducted a retrospective observational monocentric study. We built a mathematical model to predict BNP levels, using multiple linear regressions, [12].

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