---
_id: '6689'
abstract:
- lang: eng
text: "Free amino nitrogen (FAN) concentrations in beer mash can be determined with
machine learning algorithms\r\nfrom near-infrared (NIR) spectra. NIR spectroscopy
is an alternative to a classical chemical analysis and\r\nallows for the application
of inline process quality control. This study investigates the capabilities of\r\ndifferent
machine learning techniques such as Ordinary Least Squares (OLS) regression, Decision
Tree\r\nRegressor (DTR), Bayesian Ridge Regression (BRR), Ridge Regression (RR),
K-nearest neighbours (KNN)\r\nregression as well as Support Vector Regression
(SVR) to predict the FAN content in beer mash from NIR\r\nspectra. Various pre-processing
strategies such as principal component analysis (PCA) and data\r\nstandardization
were used to process NIR data that were used to train the machine learning algorithms.\r\nAlgorithm
training was conducted with NIR data obtained from 16 beer mashes with varying
FAN\r\nconcentrations. The trained models were then validated with 4 beer mashes
that were not used for model\r\ntraining. Machine learning algorithms based on
linear regression showed the highest prediction accuracy on\r\nunpre-processed
data. BRR reached a root mean square error of calibration (RMSEC) of 2.58 mg/L
(R2 = 0.96)\r\nand a prediction accuracy (RMSEP) of 2.81 mg/L (R2 = 0.96). The
FAN concentration range of the investigated\r\nsamples was between approx. 180
and 220 mg/L. Machine learning based NIR spectra analysis is an alternative\r\nto
classical chemical FAN level determination methods and can also be used as inline
sensor system."
article_type: original
author:
- first_name: Patrick
full_name: Wefing, Patrick
id: '68976'
last_name: Wefing
- first_name: Florian
full_name: Conradi, Florian
id: '68967'
last_name: Conradi
- first_name: Johannes
full_name: Rämisch, Johannes
last_name: Rämisch
- first_name: Peter
full_name: Neubauer, Peter
last_name: Neubauer
- first_name: Jan
full_name: Schneider, Jan
id: '13209'
last_name: Schneider
orcid: 0000-0001-6401-8873
citation:
ama: Wefing P, Conradi F, Rämisch J, Neubauer P, Schneider J. Determination of free
amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation
by machine learning algorithms. Brewing science . 2021;74(9/10):107-121.
doi:https://doi.org/10.23763/BrSc21-10wefing
apa: Wefing, P., Conradi, F., Rämisch, J., Neubauer, P., & Schneider, J. (2021).
Determination of free amino nitrogen in beer mash with an inline NIR transflectance
probe and data evaluation by machine learning algorithms. Brewing Science ,
74(9/10), 107–121. https://doi.org/10.23763/BrSc21-10wefing
bjps: Wefing P et al. (2021) Determination of Free Amino Nitrogen
in Beer Mash with an Inline NIR Transflectance Probe and Data Evaluation by Machine
Learning Algorithms. Brewing science 74, 107–121.
chicago: 'Wefing, Patrick, Florian Conradi, Johannes Rämisch, Peter Neubauer, and
Jan Schneider. “Determination of Free Amino Nitrogen in Beer Mash with an Inline
NIR Transflectance Probe and Data Evaluation by Machine Learning Algorithms.”
Brewing Science 74, no. 9/10 (2021): 107–21. https://doi.org/10.23763/BrSc21-10wefing.'
chicago-de: 'Wefing, Patrick, Florian Conradi, Johannes Rämisch, Peter Neubauer
und Jan Schneider. 2021. Determination of free amino nitrogen in beer mash with
an inline NIR transflectance probe and data evaluation by machine learning algorithms.
Brewing science 74, Nr. 9/10: 107–121. doi:https://doi.org/10.23763/BrSc21-10wefing,
.'
din1505-2-1: 'Wefing, Patrick ; Conradi, Florian ; Rämisch,
Johannes ; Neubauer, Peter
; Schneider, Jan: Determination
of free amino nitrogen in beer mash with an inline NIR transflectance probe and
data evaluation by machine learning algorithms. In: Brewing science Bd.
74, Carl (2021), Nr. 9/10, S. 107–121'
havard: P. Wefing, F. Conradi, J. Rämisch, P. Neubauer, J. Schneider, Determination
of free amino nitrogen in beer mash with an inline NIR transflectance probe and
data evaluation by machine learning algorithms, Brewing Science . 74 (2021) 107–121.
ieee: 'P. Wefing, F. Conradi, J. Rämisch, P. Neubauer, and J. Schneider, “Determination
of free amino nitrogen in beer mash with an inline NIR transflectance probe and
data evaluation by machine learning algorithms,” Brewing science , vol.
74, no. 9/10, pp. 107–121, 2021, doi: https://doi.org/10.23763/BrSc21-10wefing.'
mla: Wefing, Patrick, et al. “Determination of Free Amino Nitrogen in Beer Mash
with an Inline NIR Transflectance Probe and Data Evaluation by Machine Learning
Algorithms.” Brewing Science , vol. 74, no. 9/10, 2021, pp. 107–21, https://doi.org/10.23763/BrSc21-10wefing.
short: P. Wefing, F. Conradi, J. Rämisch, P. Neubauer, J. Schneider, Brewing Science 74
(2021) 107–121.
ufg: 'Wefing, Patrick u. a.: Determination of free amino nitrogen in beer
mash with an inline NIR transflectance probe and data evaluation by machine learning
algorithms, in: Brewing science 74 (2021), H. 9/10, S. 107–121.'
van: Wefing P, Conradi F, Rämisch J, Neubauer P, Schneider J. Determination of free
amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation
by machine learning algorithms. Brewing science . 2021;74(9/10):107–21.
date_created: 2021-11-02T10:06:04Z
date_updated: 2025-01-30T15:43:53Z
department:
- _id: DEP1308
- _id: DEP4028
doi: https://doi.org/10.23763/BrSc21-10wefing
intvolume: ' 74'
issue: 9/10
keyword:
- mashing
- NIR
- machine learning
- FAN
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.researchgate.net/publication/355735532_Determination_of_free_amino_nitrogen_in_beer_mash_with_an_inline_NIR_transflectance_probe_and_data_evaluation_by_machine_learning_algorithms
oa: '1'
page: 107 - 121
publication: 'Brewing science '
publication_identifier:
eissn:
- 0723-1520
issn:
- 1866-5195
publication_status: published
publisher: Carl
quality_controlled: '1'
status: public
title: Determination of free amino nitrogen in beer mash with an inline NIR transflectance
probe and data evaluation by machine learning algorithms
type: journal_article
user_id: '83781'
volume: 74
year: '2021'
...
---
_id: '12835'
abstract:
- lang: eng
text: Delayed-release dosage forms are mainly manufactured as batch processes and
include coated tablets, pellets, or particles with gastric resistant polymers.
Authors propose a novel approach using the hot-melt extrusion technique to prepare
delayed release dosage forms via a continuous manufacturing process, a new trend
in the pharmaceutical industry. A full factorial design was employed to correlate
input variables, including stearic acid (SA) content, drug content, and pellet
size with drug release properties of the pellets. PLS fit method suitably elaborated
the relationship between input and output variables with reasonably good fit and
goodness of prediction. All three input factors influenced drug release in enzyme-free
simulated gastric fluid (SGF) after 120 min; however, SA content did not significantly
affect drug dissolution in the enzyme-free simulated intestinal fluid (SIF). An
optimized formulation and design space were determined by overlaying multiple
contours established from regression equations. The continuous manufacturing process
was successfully monitored using inline near-infrared (NIR) and inline particle
size analysis, with drug load and pellet size being well-controlled within the
design space. The obtained pellets released less than 5% after 120 min in SGF
and more than 85% and 95% after 30 min and 45 min, respectively, after switching
to SIF. (C) 2020 American Pharmacists Association (R). Published by Elsevier Inc.
All rights reserved.
author:
- first_name: Anh Q.
full_name: Vo, Anh Q.
last_name: Vo
- first_name: Gerd
full_name: Kutz, Gerd
id: '12015'
last_name: Kutz
- first_name: Herman
full_name: He, Herman
last_name: He
- first_name: Sagar
full_name: Narala, Sagar
last_name: Narala
- first_name: Suresh
full_name: Bandari, Suresh
last_name: Bandari
- first_name: Michael A.
full_name: Repka, Michael A.
last_name: Repka
citation:
ama: 'Vo AQ, Kutz G, He H, Narala S, Bandari S, Repka MA. Continuous Manufacturing
of Ketoprofen Delayed Release Pellets Using Melt Extrusion Technology: Application
of QbD Design Space, Inline Near Infrared, and Inline Pellet Size Analysis. Journal
of Pharmaceutical Sciences. 2020;109(12):3598-3607. doi:10.1016/j.xphs.2020.09.007'
apa: 'Vo, A. Q., Kutz, G., He, H., Narala, S., Bandari, S., & Repka, M. A. (2020).
Continuous Manufacturing of Ketoprofen Delayed Release Pellets Using Melt Extrusion
Technology: Application of QbD Design Space, Inline Near Infrared, and Inline
Pellet Size Analysis. Journal of Pharmaceutical Sciences, 109(12),
3598–3607. https://doi.org/10.1016/j.xphs.2020.09.007'
bjps: 'Vo AQ et al. (2020) Continuous Manufacturing of Ketoprofen
Delayed Release Pellets Using Melt Extrusion Technology: Application of QbD Design
Space, Inline Near Infrared, and Inline Pellet Size Analysis. Journal of Pharmaceutical
Sciences 109, 3598–3607.'
chicago: 'Vo, Anh Q., Gerd Kutz, Herman He, Sagar Narala, Suresh Bandari, and Michael
A. Repka. “Continuous Manufacturing of Ketoprofen Delayed Release Pellets Using
Melt Extrusion Technology: Application of QbD Design Space, Inline Near Infrared,
and Inline Pellet Size Analysis.” Journal of Pharmaceutical Sciences 109,
no. 12 (2020): 3598–3607. https://doi.org/10.1016/j.xphs.2020.09.007.'
chicago-de: 'Vo, Anh Q., Gerd Kutz, Herman He, Sagar Narala, Suresh Bandari und
Michael A. Repka. 2020. Continuous Manufacturing of Ketoprofen Delayed Release
Pellets Using Melt Extrusion Technology: Application of QbD Design Space, Inline
Near Infrared, and Inline Pellet Size Analysis. Journal of Pharmaceutical Sciences
109, Nr. 12: 3598–3607. doi:10.1016/j.xphs.2020.09.007,
.'
din1505-2-1: 'Vo, Anh Q. ; Kutz,
Gerd ; He, Herman ; Narala, Sagar ; Bandari,
Suresh ; Repka, Michael A.:
Continuous Manufacturing of Ketoprofen Delayed Release Pellets Using Melt Extrusion
Technology: Application of QbD Design Space, Inline Near Infrared, and Inline
Pellet Size Analysis. In: Journal of Pharmaceutical Sciences Bd. 109. Amsterdam
[u.a.], Elsevier BV (2020), Nr. 12, S. 3598–3607'
havard: 'A.Q. Vo, G. Kutz, H. He, S. Narala, S. Bandari, M.A. Repka, Continuous
Manufacturing of Ketoprofen Delayed Release Pellets Using Melt Extrusion Technology:
Application of QbD Design Space, Inline Near Infrared, and Inline Pellet Size
Analysis, Journal of Pharmaceutical Sciences. 109 (2020) 3598–3607.'
ieee: 'A. Q. Vo, G. Kutz, H. He, S. Narala, S. Bandari, and M. A. Repka, “Continuous
Manufacturing of Ketoprofen Delayed Release Pellets Using Melt Extrusion Technology:
Application of QbD Design Space, Inline Near Infrared, and Inline Pellet Size
Analysis,” Journal of Pharmaceutical Sciences, vol. 109, no. 12, pp. 3598–3607,
2020, doi: 10.1016/j.xphs.2020.09.007.'
mla: 'Vo, Anh Q., et al. “Continuous Manufacturing of Ketoprofen Delayed Release
Pellets Using Melt Extrusion Technology: Application of QbD Design Space, Inline
Near Infrared, and Inline Pellet Size Analysis.” Journal of Pharmaceutical
Sciences, vol. 109, no. 12, 2020, pp. 3598–607, https://doi.org/10.1016/j.xphs.2020.09.007.'
short: A.Q. Vo, G. Kutz, H. He, S. Narala, S. Bandari, M.A. Repka, Journal of Pharmaceutical
Sciences 109 (2020) 3598–3607.
ufg: 'Vo, Anh Q. u. a.: Continuous Manufacturing of Ketoprofen Delayed Release
Pellets Using Melt Extrusion Technology: Application of QbD Design Space, Inline
Near Infrared, and Inline Pellet Size Analysis, in: Journal of Pharmaceutical
Sciences 109 (2020), H. 12, S. 3598–3607.'
van: 'Vo AQ, Kutz G, He H, Narala S, Bandari S, Repka MA. Continuous Manufacturing
of Ketoprofen Delayed Release Pellets Using Melt Extrusion Technology: Application
of QbD Design Space, Inline Near Infrared, and Inline Pellet Size Analysis. Journal
of Pharmaceutical Sciences. 2020;109(12):3598–607.'
date_created: 2025-04-23T08:40:12Z
date_updated: 2025-06-26T13:25:32Z
department:
- _id: DEP4028
doi: 10.1016/j.xphs.2020.09.007
external_id:
isi:
- '000590406100010'
intvolume: ' 109'
isi: '1'
issue: '12'
keyword:
- Continuous manufacturing
- Delayed-release
- FT-NIR
- Inline particle size analysis
- Hot melt extrusion
language:
- iso: eng
page: 3598-3607
place: Amsterdam [u.a.]
publication: Journal of Pharmaceutical Sciences
publication_identifier:
eissn:
- 1520-6017
issn:
- 0022-3549
publication_status: published
publisher: Elsevier BV
status: public
title: 'Continuous Manufacturing of Ketoprofen Delayed Release Pellets Using Melt
Extrusion Technology: Application of QbD Design Space, Inline Near Infrared, and
Inline Pellet Size Analysis'
type: scientific_journal_article
user_id: '83781'
volume: 109
year: '2020'
...