In vitro and in silico computational methods for assessing vaginal permeability
OBJECTIVE: Vaginal administration is an important alternative to the oral route for both topical and systemic use. Therefore, the development of reliable in silico methods for the study of drugs permeability is becoming popular in order to avoid time-consuming and costly experiments.
METHODS: In the current study, Franz cells and appropriate HPLC or ESI-Q/MS analytical methods were used to experimentally measure the apparent permeability coefficient (Papp) of 108 compounds (drugs and non-drugs). Papp values were then correlate with 75 molecular descriptors (physicochemical, structural, and pharmacokinetic) by developing two Quantitative Structure Permeability Relationship (QSPR) models, a Partial Least Square (PLS) and a Support Vector Machine (SVM). Both were validated by internal, external and cross-validation.
RESULTS: Based on the calculated statistical parameters (PLS model A: R2 = 0.673 and Q2 = 0.594, PLS model B: R2 = 0.902 and Q2 = 0.631, SVM: R2 = 0.708 and Q2 = 0.758). SVM presents higher predictability while PLS adequately interprets the theory of permeability.
CONCLUSIONS: The most important parameters for vaginal permeability were found to be the relative PSA, logP, logD, water solubility and fraction unbound (FU). Respectively, the combination of both models could be a useful tool for understanding and predicting the vaginal permeability of drug candidates.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:49 |
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| Enthalten in: |
Drug development and industrial pharmacy - 49(2023), 3 vom: 18. März, Seite 249-259 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Tsanaktsidou, Eleni [VerfasserIn] |
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| Links: |
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| Themen: |
In vitro |
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| Anmerkungen: |
Date Completed 08.05.2023 Date Revised 08.05.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1080/03639045.2023.2199071 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM355190885 |
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| 245 | 1 | 0 | |a In vitro and in silico computational methods for assessing vaginal permeability |
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| 500 | |a Date Completed 08.05.2023 | ||
| 500 | |a Date Revised 08.05.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a OBJECTIVE: Vaginal administration is an important alternative to the oral route for both topical and systemic use. Therefore, the development of reliable in silico methods for the study of drugs permeability is becoming popular in order to avoid time-consuming and costly experiments | ||
| 520 | |a METHODS: In the current study, Franz cells and appropriate HPLC or ESI-Q/MS analytical methods were used to experimentally measure the apparent permeability coefficient (Papp) of 108 compounds (drugs and non-drugs). Papp values were then correlate with 75 molecular descriptors (physicochemical, structural, and pharmacokinetic) by developing two Quantitative Structure Permeability Relationship (QSPR) models, a Partial Least Square (PLS) and a Support Vector Machine (SVM). Both were validated by internal, external and cross-validation | ||
| 520 | |a RESULTS: Based on the calculated statistical parameters (PLS model A: R2 = 0.673 and Q2 = 0.594, PLS model B: R2 = 0.902 and Q2 = 0.631, SVM: R2 = 0.708 and Q2 = 0.758). SVM presents higher predictability while PLS adequately interprets the theory of permeability | ||
| 520 | |a CONCLUSIONS: The most important parameters for vaginal permeability were found to be the relative PSA, logP, logD, water solubility and fraction unbound (FU). Respectively, the combination of both models could be a useful tool for understanding and predicting the vaginal permeability of drug candidates | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a QSPR models | |
| 650 | 4 | |a SVM and PLS | |
| 650 | 4 | |a Vaginal permeability | |
| 650 | 4 | |a in silico | |
| 650 | 4 | |a in vitro | |
| 650 | 7 | |a Pharmaceutical Preparations |2 NLM | |
| 700 | 1 | |a Krestenitis, Marios |e verfasserin |4 aut | |
| 700 | 1 | |a Karavasili, Christina |e verfasserin |4 aut | |
| 700 | 1 | |a Zacharis, Constantinos K |e verfasserin |4 aut | |
| 700 | 1 | |a Fatouros, Dimitrios G |e verfasserin |4 aut | |
| 700 | 1 | |a Markopoulou, Catherine K |e verfasserin |4 aut | |
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