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Network of statistical experts
STAT-Net is a network of academic and industry experts in the area of clinical trial design to optimize the design of Phase II and Phase III clinical trials, based on advanced statistical and pharmacological modeling and the latest biostatistical and epidemiological concepts.

STAT-Net is a pan-European network of statistical experts from both academia and industry. They share their expertise in pharmacokinetics/pharmacodynamics (PK/PD), modelling, biostatistics, infectious diseases, antimicrobial agents, microbiology, epidemiology and clinical development. With all that knowledge they investigate approaches to improve the data-driven design of Phase II and Phase III clinical trials. STAT-Net projects cover two main topics:

PK/PD Studies

Teams in Rotterdam and Bristol perform advanced PK/PD modelling studies to support more extensive use of PK/PD modelling in clinical trial design and future drug development and approval. More specifically, they are:

  • exploring the link between preclinical PK/PD predictions and the observed clinical efficacy and emergence of resistance;
  • developing popPK models to better support the design of Phase II and Phase III trials and better integrate PK data from Phase II and Phase III studies;
  • exploring exposure-response relationships and address PK/PD issues.

Statistical Methodologies

STAT-Net is also evaluating novel clinical trial design strategies based on modern biostatistical and epidemiological concepts. Aimed to increase efficiency and success rates of clinical trials. Teams in Zurich, Paris, Freiburg, and Utrecht are:

  • evaluating in depth the use of the hierarchical nested trial design (HNTD) in antibacterial trials;
  • assessing the adaptive use of limited historical control data within a Bayesian framework to shape the clinical development programs of new antibiotics;
  • providing more informative analyses of complex time-to-event patterns that can occur in randomized controlled trials of antimicrobial drugs, by adopting a simulation-based approach;
  • improving the accuracy of endpoints in severe infectious diseases.
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Key members

  • Aaron Dane

    Academic / Danestat

  • Emmanuel Weiss

    Academic / Campus Grands Moulins - Université de Paris Diderot

  • Henri van Werkhoven

    Investigator / Academic / UMC Utrecht

  • Jean-François Timsit

    Academic / Hôpital Bichat Claude-Bernard - APHP

  • Jean-Ralph Zahar

    Academic / Campus Grands Moulins - Université de Paris Diderot

  • Julien Sauser

    Academic / University Hospital Geneva

  • Kit Roes

    Professor / Academic / UMC Utrecht

  • Marlieke Kraker, de

    Epidemiologist / Academic / University Hospital Geneva

  • Marlon Grodd

    Academic / Universitätsklinikum Freiburg

  • Martin Wolkewitz

    Academic / Universitätsklinikum Freiburg

  • Stephan Harbarth

    Academic leader / University Hospital Geneva