Dissolution rate and apparent solubility of poorly soluble drugs in biorelevant dissolution media.

نویسندگان

  • Jonas H Fagerberg
  • Oksana Tsinman
  • Na Sun
  • Konstantin Tsinman
  • Alex Avdeef
  • Christel A S Bergström
چکیده

A series of poorly soluble BCS class II compounds with "grease ball" characteristics were assessed for solubility and dissolution rate in biorelevant dissolution media (BDM) with the purpose of investigating which molecular structures gain most in solubility when dissolved under physiologically relevant conditions. The compounds were studied in four media (simulated intestinal fluid in fasted (FaSSIF pH 6.5) and fed state (FeSSIF pH 5.0), and their corresponding blank buffers (FaSSIF(blk) and FeSSIF(blk))) at a temperature of 37 °C. The experimental results were used to analyze which molecular characteristics are of importance for the solubility in BDM and for in silico modeling using multivariate data analysis. It was revealed that a majority of the compounds exhibited a higher dissolution rate and higher solubility in the FaSSIF and FeSSIF than in their corresponding blank buffers. Compounds which were neutral or carried a positive charge were more soluble in FeSSIF than FaSSIF. The acidic compounds displayed clear pH dependency, although the higher concentration of solubilizing agents in FeSSIF than FaSSIF also improved the solubility. Five of the ten compounds were upgraded to BCS class I when dissolved in FaSSIF or FeSSIF, i.e., the maximum dose of these compounds given orally was soluble in 250 mL of these BDMs. Lipophilicity as described by the log D(oct) value was identified as a good predictor of the solubilization ratio (R(2) = 0.74), and computed molecular descriptors were also shown to successfully predict the solubilities in BDM for this data set. To conclude, the physiological solubility of "grease ball" molecules may be largely underestimated in in vitro solubility assays unless BDM is used. Moreover, the results herein indicate that the improvement obtained in BDM may be possible to predict from chemical features alone.

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عنوان ژورنال:
  • Molecular pharmaceutics

دوره 7 5  شماره 

صفحات  -

تاریخ انتشار 2010