2022-05020 - Alternance – Mathematical modeling of immune response to vaccines
Le descriptif de l’offre ci-dessous est en Anglais

Niveau de diplôme exigé : Bac + 5 ou équivalent

Fonction : Apprenti de la recherche

A propos du centre ou de la direction fonctionnelle

The challenge is to analyze these BIG DATA to answer clinical and biological questions by using appropriate statistical methods. With data on the machinery of a cell to the clinical status of individuals in any circumstances including in clinical trials, new tools are needed to translate information obtained from complex systems into knowledge. This has led to the field of « systems biology » and « systems medicine » by extension, which naturally takes place in the context of translational medicine that links clinical and biological research.
The statistical analysis of these data is facing several issues:

  • There are more parameters (p) to estimate than individuals (n)
  • The types/nature of data are various
  • The relationship between variables is often complex (e.g. non linear) and can change over time to tackle these issues we are developing specific approaches for these questions, often related to immunology.

The methods are mainly based on either mecanistic modeling using differential equation systems or on statistical learning methods. The general paradigm of our approach is to include as much information as available to answer a given question. This information comes from the available data but also from prior biological information available defining the structure of the model or restricting the space of the parameter values. We develop and apply our methods mainly for applications belonging to clinical research especially HIV immunology. For instance, several projects are devoted to the modelling of the response to antiretroviral treatments, immune interventions or vaccine in HIV infected patients.

Applications are provided by the Vaccine Research Institute (VRI), other teams in the research centre and the Bordeaux Hospital Clinical Trial Unit (CTU).

Contexte et atouts du poste

One “alternance” position is available to work on Mathematical modeling of immune response to vaccines at Inserm U1219 Bordeaux Population Health Center, Statistics in Systems and Translational Medicine team (SISTM) in Bordeaux (France) for a minimum period of 12 months.

The “alternant” will be under the supervision of Mélanie Prague. The SISTM is a team belonging to INSERM U1219 Bordeaux Population Health and INRIA Bordeaux Sud-Ouest research institutes. The group is dedicated to the analysis and the modelling of the data generated in epidemiology and medicine with a special focus on vaccines and immune interventions in HIV and other infectious diseases. Its expertise is mainly in biostatistics with a special emphasis on dynamical models based on ODE and statistical learning using moderately high dimensional data.

Mission confiée

Mechanistic models based on ordinary differential equations (ODE) represent an alternative approach for causal modelling (Commenges J.R.Statist.Soc.B 2009). The model is defined with three parts: i) a structural model defined by compartments that are interacting ii) a statistical model defining how the model parameters are varying across units/individuals iii) an observation model relating the observed quantities to compartments.

 

It can be used to analyze the within-host response to vaccine in experimental studies. A structural mathematical model is defined for the dynamics of the virus which is infecting susceptible cells that are producing viral particles once infected. Then, a statistical model is defined to explain the variation of parameters between individuals which could be explained by explanatory variables (X) or captured through random effects. The explanatory variables can be fixed (e.g. experimental groups) or time varying such as the immunological markers measuring the response to the vaccine. The parameters (fixed effects and variances of random effects) are estimated using standard approaches (stochastic EM algorithm).

However, this approach for analyzing the influence of X over some of the model parameters is not taking into account that a given model compartment (e.g. the virus) may itself influences. Ignoring this relationship between the virus and X may lead to a biased estimates of the effect of X. An alternative approach is to model X as a compartment of the structural model which gives the opportunity of capturing an effect of V over X and vice versa.

Principales activités

In this “alternance”, we will explore the impact of the two approaches for the validity of the estimates through simulations before applying it on the real dataset. Application to the modeling of antibodies response after Ebola vaccination (data from European project PREVAC-UP, see Pasin, Journal of Virology, 2019) as weel as after SARS-CoV-2 immunization (data from Vaccine research Institute) will be also considered.

The estimation will be based on a likelihood optimization based on the SAEM algorithm as implemented in the Lixoft Monolix suite. All development will be performed in R.

The candidate will be integrated in a team of biostatisticians and modelers working on related topics: modeling of HIV vaccine response. The candidate will benefit from a very attractive environment with computing facilities and close collaborations with mathematicians (from INRIA and INSERM research centers) and immunologists (from the Labex Vaccine Research Institute).

Compétences

The candidate must be seeking for a Master 2 degree in mathematics, statistics or preferably biostatistics. We are looking for a highly motivated candidate with an outstanding potential and a strong background in statistics and a deep interest in immunology and biological application. Proven experience in R language is required. Experience in Monolix is preferred. The ideal candidate is able to work effectively as part of a team, but also to show autonomy.

Experience in biostatistics, computational biology, immunology/Vaccinology, systems biology will be highly appreciated but not mandatory.

The expected starting date is Septembre 1st 2022. “Alternance” salary will follow Inria rates / school rates.

Avantages

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage

Rémunération

According to the current grid.