| Abstract The present study is a comparative study of three
equations, namely the Clausius–Clapeyron, Van’t Hoff and
Hildebrand (to calculate crystal–liquid fugacity ratio (CLFR)
of drug compounds), to select the best model in predicting the
intestinal absorption and develop a new classification system
based on dose number (Do) and CLFR. The required thermodynamic parameters [melting point, enthalpy of fusion
(DHm) and the differential molar heat capacity (DCpm)] were
experimentally obtained by differential scanning calorimetry.
Pharmacokinetic data [the human intestinal absorption (Fa)
and apparent permeability of Caco-2 (Papp_Caco-2)] and Do
were obtained from the literature. The highest value of CLFR
was found for diclofenac with the value of 88.78, 87.29, and
87.84 mol% from Clausius–Clapeyron, Van’t Hoff, and
Hildebrand approaches, respectively. The lowest CLFR value
was seen for memantine with the value of 14.3 9 10-17 and
26 9 10-12 mol% from Van’t Hoff and Hildebrand equations, respectively. Statistical comparison with the Wilcoxon
signed rank test showed that the CLFR values calculated by
three equations are different. CLFR values of more than
1 mol% correspond to the complete intestinal absorption
(Fa). There was a sigmoidal dependency between CLFR and
Fa
, similar to the dependency between Papp_Caco-2 and Fa. In
these modeling, the excellent correlations were obtained in all
three models as evidenced by a good coefficient of determination (r2) without a significant difference in the average
absolute error. A new classification system from Hildebrand
model based on D
o and CLFR was developed and was in
agreement with the biopharmaceutics classification system
(70.5%) and the biopharmaceutical drug disposition system
(65.6%). This modeling approach can be a valuable tool for
scientists as an alternative for intestinal permeability in the
biopharmaceutical classification system to develop new oral
drugs. The CLFR obtained from Hildebrand model is also
more convenient than the Clausius Clapeyron model, because
the former does not need to calculate DC
pm (difficult step in
calculating CLFR) for drug compounds. This new classification can help to develop the new drug product in industrial
and academic research, without necessary in vivo
experiments. |