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.
Metadaten
Author:Daniel J. Price, Anita Nair, Martin Kuentz, Jennifer B. DressmanGND, Christoph Saal
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:Universit├Ątsbibliothek Johann Christian Senckenberg
Creating Corporation:Johann Wolfgang Goethe-Universit├Ąt 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:Universit├Ątspublikationen
Licence (German):License LogoDeutsches Urheberrecht