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Jeremie Guedj

IAME UMR1137

Biostatistics, Investigation and Pharmacometrics in Infectious Diseases

jeremie.guedj@inserm.fr

Website: https://www.iame-research.center/
ORCID: 0000-0002-5534-5482
Twitter: @IAME_center

We are a group working on developing mathematical and statistical models to analyse data in infectious diseases and antimicrobial treatment. Our methodological developments support our involvement in clinical researches. We design, perform and analyse clinical trials and cohorts in order to better understand variability in response to antimicrobial agents and for prognosis assessment of infectious diseases. By making our methodological developments available as free software tools, we reach out to the community involved in the design and the analysis of clinical trials, namely biostatisticians, pharmacologists, physicians, drug companies and regulatory agencies.

Our group is made of four research axes have been defined as follows :

Axis 1. Methods in pharmacometrics (lead Emmanuelle Comets): encompasses methodological developments in nonlinear mixed effect models, with an expertise in optimising study design, developing inference methods and evaluating models with pharmacometric applications.

Axis 2. Mathematical modelling of pathogen dynamics (lead Jérémie Guedj): develops conceptual mathematical model to characterize the interactions between the host organisms (human or animal), the pathogen and the drug. The main medical areas studied are antivirals in the context of HIV/SIV, HBV/HDV, Ebola virus, SARS-CoV-2.

Axis 3. Clinical trial methodology and investigations in severe or emerging infectious diseases (lead Xavier Duval and Cédric Laouénan): provides methodological and logistical support for the conception, the analyses and the modelling of clinical trials but also to implement our own clinical trials. The main fields studied are pathophysiology, diagnosis and therapeutics (efficacy, safety) of severe and/or emerging infectious diseases.

Axis 4. Infections and anti-infectious agents during pregnancy and childhood (lead Laurent Mandelbrot): designs and performs clinical studies in the context of materno-fetal and children infections, with a focus on antiretroviral therapy in pregnancy, prevention of perinatal Cytomegalovirus infection, maternal-fetal bacterial infections, antibiotic use and prescription in childhood.

We are always happy to share our expertise in biostatistics and clinical investigation, develop models for complex data and/or help conduct experimental or human studies !

 

 

Top 5 publications

  1. Delattre R, Seurat J, Haddad F, Nguyen TT, Gaborieau B, Kane R, Dufour N, Ricard JD, Guedj *, Debarbieux. Combination of in vivo phage therapy data with in silico model highlights key parameters for treatment efficacy. Cell reports 2022, 39, 110825.
  2. Guk J, Guedj J, Burdet C, Andremont A, de Gunzburg J, Ducher A, Mentré F. Modeling the Effect of DAV132, a Novel Colon-Targeted Adsorbent, on Fecal Concentrations of Moxifloxacin and Gut Microbiota Diversity in Healthy Volunteers. Clinical Pharmacology and Therapeutics 2021, 109, 1045-1054.
  3. Néant N, Lingas G, Le Hingrat Q, Ghosn J, Engelmann I, Lepiller Q, Gaymard A, Ferré V, Hartard C, Plantier JC, Thibault V, Marlet J, Montes B, Bouiller K, Lescure FX, Timsit JF, Faure E, Poissy J, Chidiac C, Raffi F, Kimmoun A, Etienne M, Richard JC, Tattevin P, Garot D, Le Moing V, Bachelet D, Tardivon C, Duval X, Yazdanpanah Y, Mentré F, Laouénan C, Visseaux B, Guedj J. Modeling SARS-CoV-2 viral kinetics and association with mortality in hospitalized patients from the French COVID cohort. Proceedings of the National Academy of Sciences of the United States of America 2021, 118.
  4. Madelain V, Baize S, Jacquot F, Reynard S, Fizet A, Barron S, Solas C, Lacarelle B, Carbonnelle C, Mentré F, Raoul H, de Lamballerie X, Guedj J. Ebola viral dynamics in nonhuman primates provides insights into virus immuno-pathogenesis and antiviral strategies. Nature Communications 2018, 9, 4013.
  5. Comets E, Lavenu A, Lavielle M. Parameter estimation in nonlinear mixed effect models using saemix, an R implementation of the SAEM algorithm. Journal of Statistical Software 2017

Dernières publications sur HAL :