Journal article
In Situ Imaging Combined with Deep Learning for Crystallization Process Monitoring: Application to Cephalexin Production
Organic process research & development, v 25(7), pp 1670-1679
16 Jul 2021
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The online detection of a trace amount of an undesired solid phase within a crystal slurry can enable feedback control to improve product purity, decrease batch rejection, and increase process performance. Systems involving the production of one crystalline solid while suppressing the nucleation of a second solid are common, with applications to polymorphs, hydrates/solvates, chiral resolution, and byproducts. Several process analytical technologies (PATs) have already been established for system-specific detection of an undesired solid phase; this study adds to that PAT suite an image-based technique with greater generality and sensitivity than common tools such as Raman spectroscopy and focused beam reflectance measurement. In situ microscope images are analyzed with a convolutional neural network (CNN) to extract image features and classify cropped regions obtained by a sliding window as containing a single particle type or multiple particle types. As an experimental case study, the performance of the technique is evaluated using a system involving contamination of reactive crystallization of cephalexin with phenylglycine, the sparingly soluble byproduct in the enzymatic synthesis of cephalexin. A CNN, ResNet, was retrained for the classification task at hand and showed >98% accuracy on the test data, highlighting the distinct features of different crystal classes used as the basis of process monitoring.
Metrics
Details
- Title
- In Situ Imaging Combined with Deep Learning for Crystallization Process Monitoring: Application to Cephalexin Production
- Creators
- Hossein Salami - Georgia Institute of TechnologyMatthew A. McDonald - Georgia Institute of TechnologyAndreas S. Bommarius - Georgia Institute of TechnologyRonald W. Rousseau - Georgia Institute of TechnologyMartha A. Grover - Georgia Institute of Technology
- Publication Details
- Organic process research & development, v 25(7), pp 1670-1679
- Publisher
- Amer Chemical Soc
- Number of pages
- 10
- Grant note
- U01FD006484 / U.S Food and Drug Administration Center for Drug Evaluation and Research
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Chemical and Biological Engineering
- Web of Science ID
- WOS:000674929800020
- Scopus ID
- 2-s2.0-85111036011
- Other Identifier
- 991021958008204721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Chemistry, Applied
- Chemistry, Organic