Long-Term Amorphous Drug Stability Predictions Using Easily Calculated, Predicted, and Measured Parameters.

Katarzyna Nurzyńska,Peter M Fischer,Ian Dryden,James Mccabe,Clive J Roberts,Jonathan Booth

doi:10.1021/acs.molpharmaceut.5b00409

Katarzyna Nurzyńska, Peter M Fischer + Show 4 more

Open Access

https://doi.org/10.1021/acs.molpharmaceut.5b00409

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Abstract

The purpose of this study was to develop a predictive model of the amorphous stability of drugs with particular relevance for poorly water-soluble compounds. Twenty-five representative neutral poorly soluble compounds with a diverse range of physicochemical properties and chemical structures were systematically selected from an extensive library of marketed drug products. The physical stability of the amorphous form, measured over a 6 month period by the onset of crystallization of amorphous films prepared by melting and quench-cooling, was assessed using polarized light microscopy. The data were used as a response variable in a statistical model with calculated/predicted or measured molecular, thermodynamic, and kinetic parameters as explanatory variables. Several multiple linear regression models were derived, with varying balance between calculated/predicted and measured parameters. It was shown that inclusion of measured parameters significantly improves the predictive ability of the model. The best model demonstrated a prediction accuracy of 82% and included the following as parameters: melting and glass transition temperatures, enthalpy of fusion, configurational free energy, relaxation time, number of hydrogen bond donors, lipophilicity, and the ratio of carbon to heteroatoms. Good predictions were also obtained with a simpler model, which was comprised of easily acquired quantities: molecular weight and enthalpy of fusion. Statistical models are proposed to predict long-term amorphous drug stability. The models include readily accessible parameters, which are potentially the key factors influencing amorphous stability. The derived models can support faster decision making in drug formulation development.

Highlights

Amorphization[1] is a strategy that is increasingly employed to improve dissolution rates and bioavailability of poorly water-soluble drugs
Descriptors used for compound selection were chosen from a group that are known most commonly to contribute to AstraZeneca models of drug metabolism and pharmacokinetics properties of “small molecules”. These descriptors have been shown to have an impact on glass-forming ability (GFA), amorphous stability,[10,12] compound bioavailability,[14] and the stability of drugs formulated as a solid dispersions.[15]
It was found that Hf is significantly negatively correlated with amorphous stability

Summary

Introduction

Amorphization[1] is a strategy that is increasingly employed to improve dissolution rates and bioavailability of poorly water-soluble drugs. To determine a suitable formulation, typically, different drug− excipient combinations and ratios are prepared and tested This is both time-consuming and can be challenging when a limited quantity of a compound is available, as is typically the case at the early stages of drug-product development.[3] The efficiency of this screening process for a particular poorly soluble drug could be significantly improved by the development of predictive models as a basis for the rational selection of suitable manufacturing and formulation strategies.[4,5] With the current study in mind, such models could predict the stability of pure amorphous drugs at an early stage of the development based on their properties and indicate the applicability of amorphous formulation strategies

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