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    Understanding matrix-assisted continuous co-crystallization using a data mining approach in Quality by Design (QbD)

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    Paradkar_et_al_Crystal_Growth_&_Design.pdf (1.248Mb)
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    Publication date
    2020-07
    Author
    Chabalenge, Billy
    Korde, Sachin A.
    Kelly, Adrian L.
    Neagu, Daniel
    Paradkar, Anant R.
    Keyword
    Co-crystallization process
    Decision tree algorithms
    Hot melt extrusion
    Quality by Design (QbD)
    Rights
    ©2020 ACS. This document is the Accepted Manuscript version of a Published Work that appeared in final form in Crystal Growth & Design, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.cgd.0c00338.
    Peer-Reviewed
    Yes
    
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    Abstract
    The present study demonstrates the application of decision tree algorithms to the co-crystallization process. Fifty four (54) batches of carbamazepine-salicylic acid co-crystals embedded in poly(ethylene oxide) were manufactured via hot melt extrusion and characterized by powder X-ray diffraction, differnetial scanning calorimetry, and near-infrared spectroscopy. This dataset was then applied in WEKA, which is an open-sourced machine learning software to study the effect of processing temperature, screw speed, screw configuration, and poly(ethylene oxide) concentration on the percentage of co-crystal conversion. The decision trees obtained provided statistically meaningful and easy-to-interpret rules, demonstrating the potential to use the method to make rational decisions during the development of co-crystallization processes.
    URI
    http://hdl.handle.net/10454/17941
    Version
    Accepted manuscript
    Citation
    Chabalenge B, Korde S, Kelly AL et al (2020) Understanding matrix-assisted continuous co-crystallization using a data mining approach in Quality by Design (QbD). Crystal Growth & Design. 20(7): 4540-4549.
    Link to publisher’s version
    https://doi.org/10.1021/acs.cgd.0c00338
    Type
    Article
    Collections
    Engineering and Informatics Publications

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