ENBIS-26 Conference

Session

Statistics in Pharma / Healthcare: Statistical Modelling and Learning for Biomedical Systems

Sep 9, 2026, 2:30 PM

Conveners

Statistics in Pharma / Healthcare: Statistical Modelling and Learning for Biomedical Systems

• Rossella Berni (Department of Statistics, Computer Science, Applications -University of Florence)

96. Kinetic Models by Physics-Informed Statistical Learning Methods

Marco Galliani (Politecnico di Milano)

9/9/26, 2:30 PM

Statistics in Pharma / Healthcare

Accelerated stability studies are a fundamental tool in the development of pharmaceutical and vaccine products, enabling the prediction of long-term stability from short-term experiments conducted under stressed conditions. In this context, kinetic models—such as the Šesták–Berggren formulation combined with Arrhenius-type temperature dependence—are widely used to describe degradation...

126. Bayesian network-based Tikhonov MRI reconstruction

Sébastien Marmin (Laboratoire national de métrologie et d'essais)

9/9/26, 2:50 PM

Statistics in Pharma / Healthcare

Uncertainty quantification is essential for assessing the reliability of MRI reconstructions. The Network-based Tikhonov reconstruction method was demonstrated to produce excellent results in accelerated multicoils settings. However, in challenging low-field settings, where noise is high and scanners are single coil, this scheme requires a careful evaluation of its reconstruction...

139. Statistics Can Go Farther

Dr Dibyen Majumdar (University of Illinois at Chicago)

9/9/26, 3:10 PM

Statistics in Pharma / Healthcare

A pre-clinical trial for the treatment of cancer, with data analyzed by a traditional statistical method with random coefficient model, showed the significance of the treatment based on purified bacterial redox protein. A data analysis performed later, based on quantile regression, went beyond. It demonstrated the remarkable specificity of the effectiveness of experimental treatment.