R Shiny App for the Automated Deconvolution of NMR Spectra to Quantify the Solid-State Forms of Pharmaceutical Mixtures Article Swipe
Piotr Prostko
,
Jeroen A. Pikkemaat
,
Philipp Selter
,
Michail Lukaschek
,
Rainer Wechselberger
,
Tatsiana Khamiakova
,
Dirk Valkenborg
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/metabo12121248
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/metabo12121248
Bioavailability and chemical stability are important characteristics of drug products that are strongly affected by the solid-state structure of the active pharmaceutical ingredient (API). In pharmaceutical development and quality control activities, solid-state NMR (ssNMR) has proved to be an excellent tool for the detection and accurate quantification of undesired solid-state forms. To obtain correct quantitative outcomes, the resulting spectrum of an analytical sample should be deconvoluted into the individual spectra of the pure components. However, the ssNMR deconvolution is particularly challenging due to the following: the relatively large line widths that may lead to severe peak overlap, multiple spinning sidebands as a result of applying Magic Angle Spinning (MAS), and highly irregular peak shapes commonly observed in mixture spectra. To address these challenges, we created a tailored and automated deconvolution approach of ssNMR mixture spectra that involves a linear combination modelling (LCM) of previously acquired reference spectra of pure solid-state components. For optimal model performance, the template and mixture spectra should be acquired under the same conditions and experimental settings. In addition to the parameters controlling the contributions of the components in the mixture, the proposed model includes terms for spectral processing such as phase correction and horizontal shifting that are all jointly estimated via a non-linear, constrained optimisation algorithm. Finally, our novel procedure has been implemented in a fully functional and user-friendly R Shiny webtool (hence no local R installation required) that offers interactive data visualisations, manual adjustments to the automated deconvolution results, and the traceability and reproducibility of analyses.
Related Topics
Concepts
Deconvolution
Spinning
Spectral line
Biological system
Magic angle spinning
NMR spectra database
Solid-state
Active ingredient
Solid-state nuclear magnetic resonance
Stability (learning theory)
Computer science
Materials science
Chemistry
Analytical Chemistry (journal)
Algorithm
Nuclear magnetic resonance
Chromatography
Physics
Physical chemistry
Machine learning
Bioinformatics
Biology
Composite material
Astronomy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/metabo12121248
- https://www.mdpi.com/2218-1989/12/12/1248/pdf?version=1671010052
- OA Status
- gold
- Cited By
- 4
- References
- 15
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4312140488
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4312140488Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/metabo12121248Digital Object Identifier
- Title
-
R Shiny App for the Automated Deconvolution of NMR Spectra to Quantify the Solid-State Forms of Pharmaceutical MixturesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-12-10Full publication date if available
- Authors
-
Piotr Prostko, Jeroen A. Pikkemaat, Philipp Selter, Michail Lukaschek, Rainer Wechselberger, Tatsiana Khamiakova, Dirk ValkenborgList of authors in order
- Landing page
-
https://doi.org/10.3390/metabo12121248Publisher landing page
- PDF URL
-
https://www.mdpi.com/2218-1989/12/12/1248/pdf?version=1671010052Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2218-1989/12/12/1248/pdf?version=1671010052Direct OA link when available
- Concepts
-
Deconvolution, Spinning, Spectral line, Biological system, Magic angle spinning, NMR spectra database, Solid-state, Active ingredient, Solid-state nuclear magnetic resonance, Stability (learning theory), Computer science, Materials science, Chemistry, Analytical Chemistry (journal), Algorithm, Nuclear magnetic resonance, Chromatography, Physics, Physical chemistry, Machine learning, Bioinformatics, Biology, Composite material, AstronomyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 1, 2023: 2Per-year citation counts (last 5 years)
- References (count)
-
15Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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