Calculation of drug-polymer mixing enthalpy as a new screening method of precipitation inhibitors for supersaturating pharmaceutical formulations
- Supersaturating formulations are widely used to improve the oral bioavailability of poorly soluble drugs. However, supersaturated solutions are thermodynamically unstable and such formulations often must include a precipitation inhibitor (PI) to sustain the increased concentrations to ensure that sufficient absorption will take place from the gastrointestinal tract. Recent advances in understanding the importance of drug-polymer interaction for successful precipitation inhibition have been encouraging. However, there still exists a gap in how this newfound understanding can be applied to improve the efficiency of PI screening and selection, which is still largely carried out with trial and error-based approaches. The aim of this study was to demonstrate how drug-polymer mixing enthalpy, calculated with the Conductor like Screening Model for Real Solvents (COSMO-RS), can be used as a parameter to select the most efficient precipitation inhibitors, and thus realise the most successful supersaturating formulations. This approach was tested for three different Biopharmaceutical Classification System (BCS) II compounds: dipyridamole, fenofibrate and glibenclamide, formulated with the supersaturating formulation, mesoporous silica. For all three compounds, precipitation was evident in mesoporous silica formulations without a precipitation inhibitor. Of the nine precipitation inhibitors studied, there was a strong positive correlation between the drug-polymer mixing enthalpy and the overall formulation performance, as measured by the area under the concentration-time curve in in vitro dissolution experiments. The data suggest that a rank-order based approach using calculated drug-polymer mixing enthalpy can be reliably used to select precipitation inhibitors for a more focused screening. Such an approach improves efficiency of precipitation inhibitor selection, whilst also improving the likelihood that the most optimal formulation will be realised.
Author: | Daniel Joseph PriceORCiDGND, Anita NairGND, Martin KuentzORCiD, Jennifer B. DressmanGND, Christoph Saal |
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URN: | urn:nbn:de:hebis:30:3-502941 |
Place of publication: | Frankfurt am Main |
Document Type: | Preprint |
Language: | English |
Date of Publication (online): | 2019/04/30 |
Year of first Publication: | 2019 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Creating Corporation: | Johann Wolfgang Goethe-Universität Frankfurt am Main |
Release Date: | 2019/05/17 |
Tag: | Bioenabling formulations; Enthalpy; Precipitation inhibition; Screening; Supersaturation; in silico tools |
Page Number: | 37 |
First Page: | 1 |
Last Page: | 37 |
HeBIS-PPN: | 448780690 |
Institutes: | Biochemie, Chemie und Pharmazie |
Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 54 Chemie / 540 Chemie und zugeordnete Wissenschaften |
Sammlungen: | Universitätspublikationen |
Licence (German): | Deutsches Urheberrecht |