ANFIS-Driven Machine Learning Automated Platform for Cooling Crystallization Process Development-Reference-Cited by-同舟云学术

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ANFIS-Driven Machine Learning Automated Platform for Cooling Crystallization Process Development

Published:2024-04-04 Issue:4 Volume:28 Page:1129-1144
ISSN:1083-6160
Container-title:Organic Process Research & Development
language:en
Short-container-title:Org. Process Res. Dev.

Author:

Jong Cha Yong¹,Mittal Akshay¹,Tristan Geordi¹,Noller Vanessa¹,Chan Hui Ling¹^ORCID,Goh Yongkai²^ORCID,Yeap Eunice Wan Qi³,Dubbaka Srinivas Reddy³,Nagesh Harsha Rao³,Wong Shin Yee¹^ORCID

Affiliation:

1. Singapore Institute of Technology, 10 Dover Drive, 138683 Singapore

2. Applied Materials South East Asia Pte. Ltd., Applied Materials Building, 8 Upper Changi Road North, 506906 Singapore

3. Pfizer Asia Manufacturing Pte Ltd., Manufacturing Technology Development Centre (MTDC), 3 Biopolis Drive, 138623 Singapore

Funder

Agency for Science, Technology and Research

Pfizer

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.oprd.3c00505

Reference44 articles.

1. Crystallization in the Pharmaceutical Industry

2. The Challenges of Developing an API Crystallization Process for a Complex Polymorphic and Highly Solvating System. Part I

3. Recent Developments in the Crystallization Process: Toward the Pharmaceutical Industry

4. Progress in Research on Artificial Intelligence Applied to Polymorphism and Cocrystal Prediction

5. Modeling of the Crystallization Conditions for Organic Synthesis Product Purification Using Deep Learning

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