Green processing based on supercritical carbon dioxide for preparation of nanomedicine: Model development using machine learning and experimental validation Article Swipe
Saad M. Alshahrani
,
Mustafa Fahem Albaghdadi
,
Sabina Yasmin
,
Manal E. Alosaimi
,
Abdullah Alsalhi
,
Mohammed Algarni
,
Bassem F. Felemban
,
Ali Abdulhussain Fadhil
,
Ibrahim Mourad Mohammed
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.csite.2022.102620
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.csite.2022.102620
Solubility data for ANA (Anastrozole) drug in supercritical solvent was investigated in this study, and models were developed to estimate the solubility values. The main aim was to provide a predictive methodology for determination of drug solubility in wide range of operational parameters for advanced green pharmaceutical manufacture. The properties used are temperature and pressure which were considered as the models’ inputs. Modeling has been done using three models based on the support vector regression. These models include support vector regression (with polynomial kernel), boosted support vector machine with AdaBoost, and improved support vector machine with bagging. These models were evaluated after optimization, and all three models have a coefficient of determination (R2) higher than 0.98. Also considering RMSE, AdaBoosted SVR, Bagging SVR, and SVR have error rates of 2.31E-01, 4.31E-01, and 5.01E-01.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.csite.2022.102620
- OA Status
- gold
- Cited By
- 12
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4310721455
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4310721455Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.csite.2022.102620Digital Object Identifier
- Title
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Green processing based on supercritical carbon dioxide for preparation of nanomedicine: Model development using machine learning and experimental validationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-12-05Full publication date if available
- Authors
-
Saad M. Alshahrani, Mustafa Fahem Albaghdadi, Sabina Yasmin, Manal E. Alosaimi, Abdullah Alsalhi, Mohammed Algarni, Bassem F. Felemban, Ali Abdulhussain Fadhil, Ibrahim Mourad MohammedList of authors in order
- Landing page
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https://doi.org/10.1016/j.csite.2022.102620Publisher landing page
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.csite.2022.102620Direct OA link when available
- Concepts
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Support vector machine, Solubility, Machine learning, Computer science, Supercritical fluid, Least squares support vector machine, Supercritical carbon dioxide, Artificial intelligence, Process engineering, Chemistry, Engineering, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
12Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 3, 2023: 7Per-year citation counts (last 5 years)
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35Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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