SISTM

Statistics in systems biology and translationnal medicine

Details

Contact

Sandrine Darmigny

Rodolphe Thiebaut

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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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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2023 Key publications

Agniel D, Hejblum BP, Thiebaut R, Parast L. Doubly robust evaluation of high-dimensional surrogate markers. Biostatistics. 2023;24(4):985-99. https://doi.org/10.1093/biostatistics/kxac020

Alexandre M, Prague M, McLean C, Bockstal V, Douoguih M, Thiebaut R, Consortia EaE. Prediction of long-term humoral response induced by the two-dose heterologous Ad26.ZEBOV, MVA-BN-Filo vaccine against Ebola. NPJ Vaccines. 2023;8(1):174. https://doi.org/10.1038/s41541-023-00767-y

Blengio F, Hocini H, Richert L, Lefebvre C, Durand M, Hejblum B, Tisserand P, McLean C, Luhn K, Thiebaut R, Levy Y. Identification of early gene expression profiles associated with long-lasting antibody responses to the Ebola vaccine Ad26.ZEBOV/MVA-BN-Filo. Cell Rep. 2023;42(9):113101. https://doi.org/10.1016/j.celrep.2023.113101

Choi EM-L, Lacarra B, Afolabi MO, Ale BM, Baiden F, Betard C, Foster J, Hamze B, Schwimmer C, Manno D, D’Ortenzio E, Ishola D, Keita CM, Keshinro B, Njie Y, van Dijck W, Gaddah A, Anumendem D, Lowe B, Vatrinet R, Lawal BJ, Otieno GT, Samai M, Deen GF, Swaray IB, Kamara AB, Kamara MM, Diagne MA, Kowuor D, McLean C, Leigh B, Beavogui AH, Leyssen M, Luhn K, Robinson C, Douoguih M, Greenwood B, Thiebaut R, Watson-Jones D. Safety and immunogenicity of the two-dose heterologous Ad26.ZEBOV and MVA-BN-Filo Ebola vaccine regimen in infants: a phase 2, randomised, double-blind, active-controlled trial in Guinea and Sierra Leone. Lancet Glob Health. 2023;11(11):e1743-e52. https://doi.org/10.1016/S2214-109X(23)00410-2

Clairon Q, Pasin C, Balelli I, Thiebaut R, Prague M. Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: an optimal control approach. Computation Stat. 2023. https://doi.org/10.1007/s00180-023-01420-x

Clairon Q, Prague M, Planas D, Bruel T, Hocqueloux L, Prazuck T, Schwartz O, Thiebaut R, Guedj J. Modeling the kinetics of the neutralizing antibody response against SARS-CoV-2 variants after several administrations of Bnt162b2. PLoS Comput Biol. 2023;19(8):e1011282. https://doi.org/10.1371/journal.pcbi.1011282

Collin A, Hejblum BP, Vignals C, Lehot L, Thiebaut R, Moireau P, Prague M. Using a population-based Kalman estimator to model the COVID-19 epidemic in France: estimating associations between disease transmission and non-pharmaceutical interventions. Int J Biostat. 2023. https://doi.org/10.1515/ijb-2022-0087

Devaux A, Helmer C, Genuer R, Proust-Lima C. Random survival forests with multivariate longitudinal endogenous covariates. Stat Methods Med Res. 2023;32(12):2331-46. https://doi.org/10.1177/09622802231206477

Dong L, Moodie EEM, Villain L, Thiebaut R. Evaluating the Use of Generalized Dynamic Weighted Ordinary Least Squares for Individualized Hiv Treatment Strategies. Ann Appl Stat. 2023;17(3):2432-51. https://doi.org/10.1214/22-aoas1726

Freulon P, Bigot J, Hejblum BP. Cytopt: Optimal Transport with Domain Adaptation for Interpreting Flow Cytometry Data. Ann Appl Stat. 2023;17(2):1086-104. https://doi.org/10.1214/22-Aoas1660

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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