SISTM

Statistics in systems biology and translationnal medicine

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Sandrine Darmigny

Pr. Rodolphe Thiebaut
MD, PhD, SISTM Director

Rodolphe Thiebaut is a medical doctor, with specialization in Public Health. He holds a PhD in Biostatistics from Bordeaux University.

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Informations Downloads Publications

Objectives

The team is devoted to the development of statistical methods for the integrative analysis of data in medicine and biology. Thanks to the technological improvements, clinical and biological research is generating massive amounts of data. Of importance are the « omics » data such as genomics (gene expression) and proteomics but also other types of data, for which modern technologies have strongly increased the amount of information (e.g. medical imaging, cell counts).
This SISTM team is labelled by both Inserm and Inria.

The applications are carried out in collaboration with the Vaccine Research Institute (VRI), other teams from the center as well as the Methodological Support Unit for Clinical and Epidemiological Research (USMR) of the Bordeaux University Hospital.

The two main objectives of the SISTM team are:

To accelerate the development of vaccines by analyzing all the information available in early clinical trials and optimizing new trials.
To develop new data science approaches to analyze and model high dimensional data in small sample size studies.

Research area

The team is organized around three axes sharing a common objective. It is embarked in a double challenge of developing methods to deal with high dimensional data with low sample size and a main application for accelerating vaccine development.

Hence in Axis 1, the relevant information is extracted from big data. This information is used to estimate mechanistic model parameters in Axis 2. Mechanistic models can then be used for simulating the optimal vaccine strategies to be evaluated in the next clinical trials.

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Research area

Axis 1 High Dimensional Statistical Learning

To unlock the analysis of high-dimensional longitudinal data by developing suitable statistical approaches, in particular for applications to high-throughput data (e.g. microbiome, transcriptome, cytomics) generated in vaccine trials.
To leverage prior biological knowledge and formally incorporate it into statistical models to tackle the small n large p setting, one of the characteristics of early phase vaccine trials.
To advance adaptive clustering methods of high-dimensional data in both supervised and unsupervised settings, especially to infer the proportions of cellular population from gene expression measurements and also to identify gene whose expression is key in segmenting transcriptomic measurements across vaccine arms or disease severity for instance.
To perform feature selection and dimension reduction of high-dimensional molecular and cellular data, as a first step to feed such information into mechanistic models.

Axis 2 Mechanistic learning

To infer ordinary differential equations (ODE) systems parameters by using high dimensional data. We account for multiple markers measured with errors, sparsity in data sampling and inter-individual variability using non-linear mixed effects models.
To compare and implement control strategies through various approaches belonging to statistical control, stochastic control and reinforcement learning

Axis 3 Translational vaccinology

To accelerate vaccine development by in silico trials
To accelerate vaccine development by new adaptive designs
To accelerate vaccine development by in depth analysis of data generated in early clinical trials

Les applications sont réalisées en collaboration avec the Vaccine Research Institute (VRI), d’autres équipes du centre ainsi que l’Unité de Soutien Méthodologique à la Recherche Clinique et Epidémiologique (USMR) du CHU de Bordeaux

Downloads

marqLevAlg

For function optimization

VSURF

Variable Selection Using Random Forests

TcGSA

Gene set analysis of longitudinal gene expression data sets

TcGSA

Development version

R2GUESS

Graphical processing Unit Evolutionary Stochastic Search

sgPLS

Sparse Group Partial Least Square package

NPflow

Bayesian Nonparametrics for Automatic Gating of Flow-Cytometry Data

NPflow

Development version

ClogitLasso

For Lasso Estimation of Conditional Logistic
Regression Models for matched case-control and case-crossover studies

Reference Curves

For CD4+ T Cell Count Response to Combination of Antiretroviral Treatment in HIV-1 Infected Naïve Patients

2021 Key publications

Alexandre M, Prague M, Thiebaut R. Between-group comparison of area under the curve in clinical trials with censored follow-up: Application to HIV therapeutic vaccines. Stat Methods Med Res. 2021 Jul 4:9622802211023963. https://doi.org/10.1177/09622802211023963

Barry H, Mutua G, Kibuuka H, Anywaine Z, Sirima SB, Meda N, Anzala O, Eholie S, Betard C, Richert L, Lacabaratz C, McElrath MJ, De Rosa S, Cohen KW, Shukarev G, Robinson C, Gaddah A, Heerwegh D, Bockstal V, Luhn K, Leyssen M, Douoguih M, Thiebaut R, group EBLS. Safety and immunogenicity of 2-dose heterologous Ad26.ZEBOV, MVA-BN-Filo Ebola vaccination in healthy and HIV-infected adults: A randomised, placebo-controlled Phase II clinical trial in Africa. PLoS Med. 2021 Oct;18(10):e1003813. https://doi.org/10.1371/journal.pmed.1003813

Capitaine L, Genuer R, Thiebaut R. Random forests for high-dimensional longitudinal data. Stat Methods Med Res. 2021 Jan;30(1):166-84. https://doi.org/10.1177/0962280220946080

Colas C, Hejblum B, Rouillon S, Thiebaut R, Oudeyer PY, Moulin-Frier C, Prague M. EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models. J Artif Intell Res. 2021 Jul;71:479-519. https://doi.org/10.1613/jair.1.12588

Levy Y, Lacabaratz C, Lhomme E, Wiedemann A, Bauduin C, Fenwick C, Foucat E, Surenaud M, Guillaumat L, Boilet V, Rieux V, Bouchaud O, Girard PM, Molina JM, Morlat P, Hocqueloux L, Richert L, Pantaleo G, Lelievre JD, Thiebaut R. A randomized placebo-controlled efficacy study of a prime boost therapeutic vaccination strategy in HIV-1 infected individuals: VRI02 ANRS 149 LIGHT Phase II trial. J Virol. 2021 Apr 12;95(9). https://doi.org/10.1128/jvi.02165-20

Levy Y, Wiedemann A, Hejblum BP, Durand M, Lefebvre C, Surenaud M, Lacabaratz C, Perreau M, Foucat E, Dechenaud M, Tisserand P, Blengio F, Hivert B, Gauthier M, Cervantes-Gonzalez M, Bachelet D, Laouenan C, Bouadma L, Timsit JF, Yazdanpanah Y, Pantaleo G, Hocini H, Thiebaut R, French Ccsg. CD177, a specific marker of neutrophil activation, is associated with coronavirus disease 2019 severity and death. iScience. 2021 Jul 23;24(7):102711. https://doi.org/10.1016/j.isci.2021.102711

Loubet P, Wittkop L, Tartour E, Parfait B, Barrou B, Blay JY, Hourmant M, Lachatre M, Laplaud DA, Laville M, Laviolle B, Lelievre JD, Morel J, Nguyen S, Spano JP, Terrier B, Thiebaut A, Viallard JF, Vrtovsnik F, de Lamballerie X, Launay O. A French cohort for assessing COVID-19 vaccine responses in specific populations. Nat Med. 2021 Jul 12;27(8):1319-21. https://doi.org/10.1038/s41591-021-01435-1

Pollard AJ, Launay O, Lelievre JD, Lacabaratz C, Grande S, Goldstein N, Robinson C, Gaddah A, Bockstal V, Wiedemann A, Leyssen M, Luhn K, Richert L, Betard C, Gibani MM, Clutterbuck EA, Snape MD, Levy Y, Douoguih M, Thiebaut R, group EEs. Safety and immunogenicity of a two-dose heterologous Ad26.ZEBOV and MVA-BN-Filo Ebola vaccine regimen in adults in Europe (EBOVAC2): a randomised, observer-blind, participant-blind, placebo-controlled, phase 2 trial. Lancet Infect Dis. 2021 Apr;21(4):493-506. https://doi.org/10.1016/S1473-3099(20)30476-X

Zhang HG, Hejblum BP, Weber GM, Palmer NP, Churchill SE, Szolovits P, Murphy SN, Liao KP, Kohane IS, Cai T. ATLAS: an automated association test using probabilistically linked health records with application to genetic studies. J Am Med Inform Assoc. 2021 Nov 25;28(12):2582-92. https://doi.org/10.1093/jamia/ocab187

Prague M, Lavielle M. SAMBA: A novel method for fast automatic model building in nonlinear mixed-effects models. CPT Pharmacometrics Syst Pharmacol. 2022 Feb 1;11(2):161-72. https://doi.org/10.1002/psp4.12742

View all of the team’s publications in Oskar

Last News

Posted on : 20 Jun 2023

The BPH SISTM team is accredited by both Inria & Inserm

Team

The SISTM team – © Inria / Photo F. Stucin The BPH SISTM team is accredited by both Inria & Inserm The two main objectives of the SISTM team (Statistics in Systems biology and Translationnal Medicine), led by Pr Rodolphe Thiébaut, are: i) to accelerate the development of vaccines by analyzing all the information available […]

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Posted on : 02 Jan 2023

More than 3 M€ for our project UB 2030 CAP Digital Health labellized by the call AMI CMA "Skills and future professions" of the 2030 France national plan

Awards

This new project coordinated by Rodolphe Thiébaut leader of the BPH’s SISTM team, is part of the 70 awarded of the second call for expression of interest AMI CMA 2022. The ambition is to offer innovative training schemes in the field of digital health. The project UB 2030 CAP Digital Health brings together a large […]

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