Abstract

Introduction and objectives: In moving from batch to continuous manufacturing of pharmaceutical products, knowledge of all experimental variables is required to help control and achieve a stable system that yields a consistent product with the desired attributes. Spectroscopic tools are often used to provide point measurements at key points in the process. Here we demonstrate the applicability of Hyperspectral Imaging (HSI) to continuous nuclaetion processes. The objective of the work described here was to show how HSI can be used to monitor mixing processes by providing spatially discriminated near-infrared spectra, yielding vital process information that has only previously been estimated using simulation techniques such as computational fluid dynamics (CFD). Methods: Water (antisolvent) and an IPA/water mixture (solvent) containing dissolved paracetamol seed crystals were mixed in a tube by introducing the antisolvent jet at different flow rates, and the resulting mixing in the tube was imaged with an InnoSpec RedEye camera in the spectral range 950 to 1700 nm. Microscope images of the resultant crystals from each different flow rate were taken to confirm that differences in the final crystal product were observed. Machine learning techniques in the form of Support Vector Machine (SVM) analysis were used to analyse and automatically separate the spectral data of the solvent/antisolvent mix into the different components. Results: The antisolvent jet, which resulted in nucleation near the point of injection, could clearly be identified and therefore monitored after application of the SVM. Differences between different flow rates and concentrations were observed from the hyperspectral images obtained, and these differences carried through to the shape and size of the final crystals obtained. Conclusions: We have demonstrated the applicability of HSI and advanced data processing techniques to the monitoring of mixing dynamics, in particular those used in continuous pharmaceutical processing such as solvent/antisolvent crystallisation.

Conference

ConferenceSolving problems with spectral imaging
CountryUnited Kingdom
CityLondon
Period4/02/164/02/16
Internet address

Fingerprint

Crystals
Flow rate
Processing
Pharmaceutical Preparations
Support vector machines
Water
Hydrodynamics
Acetaminophen
Crystallization
Learning systems
Computational fluid dynamics
Injections
Microscopes
Nucleation
Cameras
Infrared radiation
Hyperspectral imaging
Monitoring
Support Vector Machine
Machine Learning

Keywords

  • pharmaceutical monitoring
  • hyperspectral imaging
  • batch crystalising

Cite this

Dziewierz, J., McGinty, J., Macfhionnghaile, P., Svoboda, V., Sefcik, J., Gachagan, A., ... Cleary, A. (2016). Applying hyperspectral imaging to continuous processing of pharmaceuticals. Poster session presented at Solving problems with spectral imaging , London, United Kingdom.
Dziewierz, Jerzy ; McGinty, John ; Macfhionnghaile, Pol ; Svoboda, Vaclav ; Sefcik, Jan ; Gachagan, Anthony ; Nordon, Alison ; Marshall, Stephen ; Cleary, Alison. / Applying hyperspectral imaging to continuous processing of pharmaceuticals. Poster session presented at Solving problems with spectral imaging , London, United Kingdom.1 p.
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abstract = "Introduction and objectives: In moving from batch to continuous manufacturing of pharmaceutical products, knowledge of all experimental variables is required to help control and achieve a stable system that yields a consistent product with the desired attributes. Spectroscopic tools are often used to provide point measurements at key points in the process. Here we demonstrate the applicability of Hyperspectral Imaging (HSI) to continuous nuclaetion processes. The objective of the work described here was to show how HSI can be used to monitor mixing processes by providing spatially discriminated near-infrared spectra, yielding vital process information that has only previously been estimated using simulation techniques such as computational fluid dynamics (CFD). Methods: Water (antisolvent) and an IPA/water mixture (solvent) containing dissolved paracetamol seed crystals were mixed in a tube by introducing the antisolvent jet at different flow rates, and the resulting mixing in the tube was imaged with an InnoSpec RedEye camera in the spectral range 950 to 1700 nm. Microscope images of the resultant crystals from each different flow rate were taken to confirm that differences in the final crystal product were observed. Machine learning techniques in the form of Support Vector Machine (SVM) analysis were used to analyse and automatically separate the spectral data of the solvent/antisolvent mix into the different components. Results: The antisolvent jet, which resulted in nucleation near the point of injection, could clearly be identified and therefore monitored after application of the SVM. Differences between different flow rates and concentrations were observed from the hyperspectral images obtained, and these differences carried through to the shape and size of the final crystals obtained. Conclusions: We have demonstrated the applicability of HSI and advanced data processing techniques to the monitoring of mixing dynamics, in particular those used in continuous pharmaceutical processing such as solvent/antisolvent crystallisation.",
keywords = "pharmaceutical monitoring, hyperspectral imaging, batch crystalising",
author = "Jerzy Dziewierz and John McGinty and Pol Macfhionnghaile and Vaclav Svoboda and Jan Sefcik and Anthony Gachagan and Alison Nordon and Stephen Marshall and Alison Cleary",
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month = "2",
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note = "Solving problems with spectral imaging ; Conference date: 04-02-2016 Through 04-02-2016",
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Dziewierz, J, McGinty, J, Macfhionnghaile, P, Svoboda, V, Sefcik, J, Gachagan, A, Nordon, A, Marshall, S & Cleary, A 2016, 'Applying hyperspectral imaging to continuous processing of pharmaceuticals' Solving problems with spectral imaging , London, United Kingdom, 4/02/16 - 4/02/16, .

Applying hyperspectral imaging to continuous processing of pharmaceuticals. / Dziewierz, Jerzy; McGinty, John; Macfhionnghaile, Pol; Svoboda, Vaclav; Sefcik, Jan; Gachagan, Anthony; Nordon, Alison; Marshall, Stephen; Cleary, Alison.

2016. Poster session presented at Solving problems with spectral imaging , London, United Kingdom.

Research output: Contribution to conferencePoster

TY - CONF

T1 - Applying hyperspectral imaging to continuous processing of pharmaceuticals

AU - Dziewierz, Jerzy

AU - McGinty, John

AU - Macfhionnghaile, Pol

AU - Svoboda, Vaclav

AU - Sefcik, Jan

AU - Gachagan, Anthony

AU - Nordon, Alison

AU - Marshall, Stephen

AU - Cleary, Alison

PY - 2016/2/4

Y1 - 2016/2/4

N2 - Introduction and objectives: In moving from batch to continuous manufacturing of pharmaceutical products, knowledge of all experimental variables is required to help control and achieve a stable system that yields a consistent product with the desired attributes. Spectroscopic tools are often used to provide point measurements at key points in the process. Here we demonstrate the applicability of Hyperspectral Imaging (HSI) to continuous nuclaetion processes. The objective of the work described here was to show how HSI can be used to monitor mixing processes by providing spatially discriminated near-infrared spectra, yielding vital process information that has only previously been estimated using simulation techniques such as computational fluid dynamics (CFD). Methods: Water (antisolvent) and an IPA/water mixture (solvent) containing dissolved paracetamol seed crystals were mixed in a tube by introducing the antisolvent jet at different flow rates, and the resulting mixing in the tube was imaged with an InnoSpec RedEye camera in the spectral range 950 to 1700 nm. Microscope images of the resultant crystals from each different flow rate were taken to confirm that differences in the final crystal product were observed. Machine learning techniques in the form of Support Vector Machine (SVM) analysis were used to analyse and automatically separate the spectral data of the solvent/antisolvent mix into the different components. Results: The antisolvent jet, which resulted in nucleation near the point of injection, could clearly be identified and therefore monitored after application of the SVM. Differences between different flow rates and concentrations were observed from the hyperspectral images obtained, and these differences carried through to the shape and size of the final crystals obtained. Conclusions: We have demonstrated the applicability of HSI and advanced data processing techniques to the monitoring of mixing dynamics, in particular those used in continuous pharmaceutical processing such as solvent/antisolvent crystallisation.

AB - Introduction and objectives: In moving from batch to continuous manufacturing of pharmaceutical products, knowledge of all experimental variables is required to help control and achieve a stable system that yields a consistent product with the desired attributes. Spectroscopic tools are often used to provide point measurements at key points in the process. Here we demonstrate the applicability of Hyperspectral Imaging (HSI) to continuous nuclaetion processes. The objective of the work described here was to show how HSI can be used to monitor mixing processes by providing spatially discriminated near-infrared spectra, yielding vital process information that has only previously been estimated using simulation techniques such as computational fluid dynamics (CFD). Methods: Water (antisolvent) and an IPA/water mixture (solvent) containing dissolved paracetamol seed crystals were mixed in a tube by introducing the antisolvent jet at different flow rates, and the resulting mixing in the tube was imaged with an InnoSpec RedEye camera in the spectral range 950 to 1700 nm. Microscope images of the resultant crystals from each different flow rate were taken to confirm that differences in the final crystal product were observed. Machine learning techniques in the form of Support Vector Machine (SVM) analysis were used to analyse and automatically separate the spectral data of the solvent/antisolvent mix into the different components. Results: The antisolvent jet, which resulted in nucleation near the point of injection, could clearly be identified and therefore monitored after application of the SVM. Differences between different flow rates and concentrations were observed from the hyperspectral images obtained, and these differences carried through to the shape and size of the final crystals obtained. Conclusions: We have demonstrated the applicability of HSI and advanced data processing techniques to the monitoring of mixing dynamics, in particular those used in continuous pharmaceutical processing such as solvent/antisolvent crystallisation.

KW - pharmaceutical monitoring

KW - hyperspectral imaging

KW - batch crystalising

UR - http://www.jpag.org/?p=meetings&r=73

M3 - Poster

ER -

Dziewierz J, McGinty J, Macfhionnghaile P, Svoboda V, Sefcik J, Gachagan A et al. Applying hyperspectral imaging to continuous processing of pharmaceuticals. 2016. Poster session presented at Solving problems with spectral imaging , London, United Kingdom.