2023 AIChE Annual Meeting

Session: Data-driven approaches, ML/AI and model uncertainty to better process understanding

Chair

Co-Chairs

Steven Ferguson, University College Dublin

Presentations

03:30 PM

(628a) Application of Experimental Design Via Bayesian Optimization (EDBO) to Pharmaceutical Process Characterization and Control Strategy Design
Jose Tabora, Michael Williams, Jason Stevens, Jiayi Fu, Jun Li, Damian Reyes-Luyanda, Dimitri Skliar

03:55 PM

(628b) Leveraging Small Data for Enhanced Process Development
Daniela Blanco

04:20 PM

(628c) Development of Experimentally Validated Machine Learning (ML) Based Model to Predict the Thawing Time of Biologics during Large Scale Freeze-Thawing Cycles
Venkatraman Nagarajan, Bodhisattwa Chaudhuri, Tibo Duran, Tanu Mehta, Yangchao Luo, Yi Wang, Bruna Minatovicz, Lauren Fontana

04:45 PM

(628d) Predictive Modeling for Glycan Method Analysis and Species Prediction
Apoorva Nisal, Frantz Gabeau, Kevin Miller

05:10 PM

(628e) Optimal Reaction Pathway Design Using Computer-Aided Process Chemistry
Shinje Lee, Klavs F. Jensen

05:35 PM

(628g) Verification, Validation, and Uncertainty Quantification for Computational Modeling and Simulation in the Pharmaceutical Industry
Ross Kenyon, Chadakarn Sirasitthichoke, Marc Horner, Mazaher Molaei Chalchooghi, Bettina Knapp