Data‐driven tools for the optimization of a pharmaceutical process through its knowledge‐driven model-Reference-Cited by-同舟云学术

Data‐driven tools for the optimization of a pharmaceutical process through its knowledge‐driven model

Published:2022-11-22 Issue:4 Volume:69 Page:
ISSN:0001-1541
Container-title:AIChE Journal
language:en
Short-container-title:AIChE Journal

Author:

Castaldello Christopher¹,Facco Pierantonio¹,Bezzo Fabrizio¹^ORCID,Georgakis Christos²^ORCID,Barolo Massimiliano¹^ORCID

Affiliation:

1. CAPE‐Lab – Computer‐Aided Process Engineering Laboratory, Department of Industrial Engineering University of Padova Padova Italy

2. Department of Chemical and Biological Engineering & Systems Research Institute for Chemical and Biological Processes Tufts University Medford Massachusetts USA

Funder

Università degli Studi di Padova

Publisher

Wiley

Subject

General Chemical Engineering,Environmental Engineering,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aic.17925

Reference19 articles.

1. Primary Drying Optimization in Pharmaceutical Freeze-Drying: A Multivial Stochastic Modeling Framework

2. A Model-Based Framework to Optimize Pharmaceuticals Freeze Drying

3. Aggressive conditions during primary drying as a contemporary approach to optimise freeze-drying cycles of biopharmaceuticals

4. Accelerating the Development and Transfer of Freeze-Drying Operations for the Manufacturing of Biopharmaceuticals by Model-Based Design of Experiments

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