Uncertainty back-propagation in PLS model inversion for design space determination in pharmaceutical product development. - Gabriele Bano; Pierantonio Facco; Natascia Meneghetti; Fabrizio Bezzo; Massimiliano Barolo (Comput. Chem. Eng., 2017)

A novel and systematic approach to identify the design space of pharmaceutical processes. - Gabriele Bano; Zilong Wang 008; Pierantonio Facco; Fabrizio Bezzo; Massimiliano Barolo; Marianthi Ierapetritou (Comput. Chem. Eng., 2018)

Design space maintenance by online model adaptation in pharmaceutical manufacturing. - Gabriele Bano; Pierantonio Facco; Marianthi Ierapetritou; Fabrizio Bezzo; Massimiliano Barolo (Comput. Chem. Eng., 2019)

An exploratory model-based design of experiments approach to aid parameters identification and reduce model prediction uncertainty. - Francesca Cenci; Arun Pankajakshan; Pierantonio Facco; Federico Galvanin (Comput. Chem. Eng., 2023)

Data fusion of Raman spectra in MSPC for fault detection and diagnosis in pharmaceutical manufacturing. - Isabella Jul-Jørgensen; Pierantonio Facco; Krist V. Gernaey; Massimiliano Barolo; Christian A. Hundahl (Comput. Chem. Eng., 2024)

On the use of machine learning to generate in-silico data for batch process monitoring under small-data scenarios. - Luca Gasparini 003; Antonio Benedetti; Giulia Marchese; Connor Gallagher; Pierantonio Facco; Massimiliano Barolo (Comput. Chem. Eng., 2024)