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Event info
Date:21 Apr
Time:9:00 - 11:00
Venue:Medicon Valley Alliance, Copenhagen
Contact person
Mia Ritterband-Rosenbaum

Mia Ritterband-Rosenbaum

Event Manager & PA to CEO

+45 21 63 38 88

MVA Good Morning Meeting “Generalized Pairwise Comparisons (GPC) – An innovative statistical method to design and analyze clinical trials”

Generalized Pairwise Comparison (GPC) is an innovative statistical method used to design and analyze clinical trials to make the best possible use of the data collected.

This allows the analysis to take into account several endpoints, providing deeper insights into the net treatment benefits.

Specifically, the GPC method enables you to:

  • Assess clinical trials based on multiple endpoints leading to increased power
  • Conduct meaningful risk:benefit analyses


Key takeaways

During this presentation, the participant will:

  • Understand how this method can be used to evaluate multiple endpoints
  • Identify when this statistical method can be applied to certain therapy areas (e.g. rare diseases)
  • Gain insights into how this approach will ultimately lead to truly “patient-centric medicine”


Date: Thursday,  April 21st, 2022
Time: 9:00 – 11:00 CET
Venue: Medicon Valley Alliance, Arne Jacobsens Allé 15, 2300 Copenhagen S, Denmark – Meeting room: Auditorium





9:00 Networking, registration and light breakfast
9:30 Welcome
David Munis Zepernick, Head of Member Engagement and Communication, Medicon Valley Alliance
Erik Falvey, Senior Director Business Development Europe at the International Drug Development Institute, IDDI
9:35 Generalized Pairwise Comparisons (GPC) – An innovative statistical method to design and analyze clinical trials
Vaiva Deltuvaite-Thomas, MS, Research Biostatistician, IDDI
10:20 Q&A
10:30 Networking
11:00 End of Good Morning Meeting



Vaiva Deltuvaite-Thomas, MS, Research Biostatistician, IDDI

Vaiva Deltuvaite-Thomas is Research Statistician at International Drug Development Institute, IDDI. Her research focuses on Generalized Pairwise Comparisons based methods in multivariate data analysis, with or without missingness/censoring.

After 15 years working as a Community Pharmacist in Lithuania, Belgium, Ireland, and France, the need to understand and explain increasing amounts of drug and treatment related information, and more importantly mis-information, has led Vaiva to joining and completing the Master program in biostatistics at Hasselt University (Belgium). Currently, she is also a PhD candidate at Hasselt University.


Target audience

Statisticians and other professionals involved in the design and analysis of clinical trials.


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