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A Practical Method to Predict Physical Stability of Amorphous Solid Dispersions

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ABSTRACT

Purpose

To predict the crystallization time of amorphous solid dispersions by controlling the combined effect of temperature and moisture content.

Methods

The authors exposed amorphous samples of spray-dried API and Hydroxypropylmethylcellulose Phtalate to various temperature and humidity conditions below and above the glass transition temperature (Tg) until crystallization of the API was observed. The crystallization of API was detected by XRPD, while the T g and the water absorption by the amorphous dispersion are quantified by mDSC and water sorption analysis.

Results

Extrapolation of the data obtained at a temperature above T g to conditions below T g gives only a qualitative trend. By contrast, in conditions below T g the logarithm of onset of crystallization time was shown to vary linearly with the T g /T ratio. A statistical analysis shows that the data obtained in the highest temperature/humidity conditions, for which the onset of crystallization is below 3 months, can be extrapolated over 15 months.

Conclusions

The proposed methodology can be used as a stress program to predict long-term stability from a relatively short observation period and to design appropriate temperature and humidity conditions for long-term storage to prevent crystallization.

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ACKNOWLEDGMENTS & DISCLOSURES

We acknowledge Marc-Antoine Perrin, Fabrice Tamagnan, Nancy Midoux, Cécile Bonvoisin, Lionel Gerbeau for their contribution to the SA project. We acknowledge Jean Alié, Jérome Menegotto, Marc Descamps, Rama Shmeis and Sophie-Dorothée Clas for their fruitful remarks and discussions.

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Authors and Affiliations

  1. Sanofi, Vitry-sur-Seine, France

    Stéphanie Greco, Jean-René Authelin, Caroline Leveder & Audrey Segalini

Authors
  1. Stéphanie Greco
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  2. Jean-René Authelin
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  3. Caroline Leveder
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  4. Audrey Segalini
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Corresponding author

Correspondence to Stéphanie Greco.

Appendix: Statistical Calculations

Appendix: Statistical Calculations

Data Pooling

The first question was: can we consider that the data obtained at 75, 80 and 100% RH is a unique population? A preliminary Analysis Of Covariance (ANCOVA) was conducted to test whether the data of the different %RH storage conditions could be pooled.

The table of ANCOVA (Table X) shows that the points (T g /T, log 10(tmc)) for the different humidity conditions can be considered from a statistical point of view as the same population. The first important conclusion, is that the %RH impact should be taken into account only once in the calculation of T g .

Table X Table of ANCOVA: Type 3 Tests of Fixed Effects
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As illustration, we show the 3 different linear regressions for the different %RH on the same graph, see Fig. 14.

Fig. 14
figure 14

Linear regression of the tm as a function of T g /T.

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Greco, S., Authelin, JR., Leveder, C. et al. A Practical Method to Predict Physical Stability of Amorphous Solid Dispersions. Pharm Res 29, 2792–2805 (2012). https://doi.org/10.1007/s11095-012-0717-5

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  • DOI: https://doi.org/10.1007/s11095-012-0717-5

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