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Eur J Pharm Sci. 2019 Apr 30;132:142-156. doi: 10.1016/j.ejps.2019.03.006. Epub 2019 Mar 12.

Calculation of drug-polymer mixing enthalpy as a new screening method of precipitation inhibitors for supersaturating pharmaceutical formulations.

Author information

1
Merck KGaA, Darmstadt, Germany; Frankfurt Goethe University, Frankfurt, Germany.
2
Merck KGaA, Darmstadt, Germany.
3
University of Applied Sciences and Arts Northwestern Switzerland, Institute of Pharma Technology, Muttenz, Switzerland.
4
Frankfurt Goethe University, Frankfurt, Germany.
5
Merck KGaA, Darmstadt, Germany. Electronic address: Christoph.saal@merckgroup.com.

Abstract

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 realize 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 realized.

KEYWORDS:

Bioenabling formulations; Enthalpy; Precipitation inhibition; Screening; Supersaturation; in silico tools

PMID:
30877067
DOI:
10.1016/j.ejps.2019.03.006

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