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    Near infra red spectroscopy as a multivariate process analytical tool for predicting pharmaceutical co-crystal concentration

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    Publication date
    2016-09-10
    Author
    Wood, Clive
    Alwati, Abdolati
    Halsey, S.A.
    Gough, Timothy D.
    Brown, Elaine C.
    Kelly, Adrian L.
    Paradkar, Anant R.
    Keyword
    Co-crystal; NIR spectroscopy; Partial Least Squares; Prediction; Active pharmaceutical ingredient; Process analytical tool
    Rights
    © 2016 The Authors. Published by Elsevier. This work is licensed under a Creative Commons Attribution 4.0 International License. http://creativecommons.org/licenses/by/4.0/
    Peer-Reviewed
    yes
    
    Metadata
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    Abstract
    The use of near infra red spectroscopy to predict the concentration of two pharmaceutical co-crystals; 1:1 ibuprofen – nicotinamide (IBU-NIC) and 1:1 carbamazepine – nicotinamide (CBZ-NIC) has been evaluated. A Partial Least Squares (PLS) regression model was developed for both co-crystal pairs using sets of standard samples to create calibration and validation data sets with which to build and validate the models. Parameters such as the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP) and correlation coefficient were used to assess the accuracy and linearity of the models. Accurate PLS regression models were created for both co-crystal pairs which can be used to predict the co-crystal concentration in a powder mixture of the co-crystal and the active pharmaceutical ingredient (API). The IBU-NIC model had smaller errors than the CBZ-NIC model, possibly due to the complex CBZ-NIC spectra which could reflect the different arrangement of hydrogen bonding associated with the co-crystal compared to the IBU-NIC co-crystal. These results suggest that NIR spectroscopy can be used as a PAT tool during a variety of pharmaceutical co-crystal manufacturing methods and the presented data will facilitate future offline and in-line NIR studies involving pharmaceutical co-crystals.
    URI
    http://hdl.handle.net/10454/8494
    Version
    Accepted Manuscript
    Citation
    Wood C, Alwati A, Halsey S, Gough T, Brown EC, Kelly AL and Paradkar AR (2016) Near infra red spectroscopy as a multivariate process analytical tool for predicting pharmaceutical co-crystal concentration. Journal of Pharmaceutical and Biomedical Analysis. 129: 172-181.
    Link to publisher’s version
    http://dx.doi.org/10.1016/j.jpba.2016.06.010
    Type
    Article
    Collections
    Life Sciences Publications
    Engineering and Informatics Publications

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