A pharmaceutical-related molecules dataset for reversed-phase chromatography retention time prediction built on combining pH and gradient time conditions
There is a rising interest in the modeling and predicting of chromatographic retention. The progress towards more complex and comprehensive models emphasized the need for broad reliable datasets. The present dataset comprises small pharmaceutical compounds selected to cover a wide range in terms of...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-06-01
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| Series: | Data in Brief |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340922002281 |
| _version_ | 1811240498228101120 |
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| author | Thomas Van Laethem Priyanka Kumari Philippe Hubert Marianne Fillet Pierre-Yves Sacré Cédric Hubert |
| author_facet | Thomas Van Laethem Priyanka Kumari Philippe Hubert Marianne Fillet Pierre-Yves Sacré Cédric Hubert |
| author_sort | Thomas Van Laethem |
| collection | DOAJ |
| description | There is a rising interest in the modeling and predicting of chromatographic retention. The progress towards more complex and comprehensive models emphasized the need for broad reliable datasets. The present dataset comprises small pharmaceutical compounds selected to cover a wide range in terms of physicochemical properties that are known to impact the retention in reversed-phase liquid chromatography. Moreover, this dataset was analyzed at five pH with two gradient slopes. It provides a reliable dataset with a diversity of conditions and compounds to support the building of new models. To enhance the robustness of the dataset, the compounds were injected individually, and each sequence of injections included a quality control sample. This unambiguous detection of each compound as well as a systematic analysis of a quality control sample ensured the quality of the reported retention times. Moreover, three different liquid chromatographic systems were used to increase the robustness of the dataset. |
| first_indexed | 2024-04-12T13:21:21Z |
| format | Article |
| id | doaj.art-014892a2dae54648876fe52c3114efa2 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-12T13:21:21Z |
| publishDate | 2022-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-014892a2dae54648876fe52c3114efa22022-12-22T03:31:28ZengElsevierData in Brief2352-34092022-06-0142108017A pharmaceutical-related molecules dataset for reversed-phase chromatography retention time prediction built on combining pH and gradient time conditionsThomas Van Laethem0Priyanka Kumari1Philippe Hubert2Marianne Fillet3Pierre-Yves Sacré4Cédric Hubert5Laboratory for the Analysis of Medicines, University of Liège (ULiege), CIRM, B36 Tower 4 (route 688 CHU) +3, Avenue Hippocrate, 15, Liège 4000, Belgium; Laboratory of Pharmaceutical Analytical Chemistry, University of Liège (ULiege), CIRM, B36 Tower 4 (route 688 CHU) +2, Avenue Hippocrate, 15, Liège 4000, Belgium; Corresponding author at: Laboratory of Pharmaceutical Analytical Chemistry, University of Liège (ULiege), CIRM, B36 Tower 4 (route 688 CHU) +2, Avenue Hippocrate, 15, Liège 4000, Belgium.Laboratory for the Analysis of Medicines, University of Liège (ULiege), CIRM, B36 Tower 4 (route 688 CHU) +3, Avenue Hippocrate, 15, Liège 4000, Belgium; Laboratory of Pharmaceutical Analytical Chemistry, University of Liège (ULiege), CIRM, B36 Tower 4 (route 688 CHU) +2, Avenue Hippocrate, 15, Liège 4000, BelgiumLaboratory of Pharmaceutical Analytical Chemistry, University of Liège (ULiege), CIRM, B36 Tower 4 (route 688 CHU) +2, Avenue Hippocrate, 15, Liège 4000, BelgiumLaboratory for the Analysis of Medicines, University of Liège (ULiege), CIRM, B36 Tower 4 (route 688 CHU) +3, Avenue Hippocrate, 15, Liège 4000, BelgiumLaboratory of Pharmaceutical Analytical Chemistry, University of Liège (ULiege), CIRM, B36 Tower 4 (route 688 CHU) +2, Avenue Hippocrate, 15, Liège 4000, BelgiumLaboratory of Pharmaceutical Analytical Chemistry, University of Liège (ULiege), CIRM, B36 Tower 4 (route 688 CHU) +2, Avenue Hippocrate, 15, Liège 4000, BelgiumThere is a rising interest in the modeling and predicting of chromatographic retention. The progress towards more complex and comprehensive models emphasized the need for broad reliable datasets. The present dataset comprises small pharmaceutical compounds selected to cover a wide range in terms of physicochemical properties that are known to impact the retention in reversed-phase liquid chromatography. Moreover, this dataset was analyzed at five pH with two gradient slopes. It provides a reliable dataset with a diversity of conditions and compounds to support the building of new models. To enhance the robustness of the dataset, the compounds were injected individually, and each sequence of injections included a quality control sample. This unambiguous detection of each compound as well as a systematic analysis of a quality control sample ensured the quality of the reported retention times. Moreover, three different liquid chromatographic systems were used to increase the robustness of the dataset.http://www.sciencedirect.com/science/article/pii/S2352340922002281High performance liquid chromatographySmall pharmaceutical compoundsReverse phase liquid chromatographyQuantitative structure retention relationship |
| spellingShingle | Thomas Van Laethem Priyanka Kumari Philippe Hubert Marianne Fillet Pierre-Yves Sacré Cédric Hubert A pharmaceutical-related molecules dataset for reversed-phase chromatography retention time prediction built on combining pH and gradient time conditions Data in Brief High performance liquid chromatography Small pharmaceutical compounds Reverse phase liquid chromatography Quantitative structure retention relationship |
| title | A pharmaceutical-related molecules dataset for reversed-phase chromatography retention time prediction built on combining pH and gradient time conditions |
| title_full | A pharmaceutical-related molecules dataset for reversed-phase chromatography retention time prediction built on combining pH and gradient time conditions |
| title_fullStr | A pharmaceutical-related molecules dataset for reversed-phase chromatography retention time prediction built on combining pH and gradient time conditions |
| title_full_unstemmed | A pharmaceutical-related molecules dataset for reversed-phase chromatography retention time prediction built on combining pH and gradient time conditions |
| title_short | A pharmaceutical-related molecules dataset for reversed-phase chromatography retention time prediction built on combining pH and gradient time conditions |
| title_sort | pharmaceutical related molecules dataset for reversed phase chromatography retention time prediction built on combining ph and gradient time conditions |
| topic | High performance liquid chromatography Small pharmaceutical compounds Reverse phase liquid chromatography Quantitative structure retention relationship |
| url | http://www.sciencedirect.com/science/article/pii/S2352340922002281 |
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