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Computational prediction of drug solubility in fasted simulated and aspirated human intestinal fluid.

Fagerberg JH, Karlsson E, Ulander J, Hanisch G, Bergström CA - Pharm. Res. (2014)

Bottom Line: Modest relationships between Sapp in PhBpH6.5 and FaSSIF (R(2) = 0.61) or HIF (R(2) = 0.62) were found.Accuracy improved when solubility in PhBpH6.5 was added as a descriptor (FaSSIF, R(2) = 0.76 and RMSETe of 0.65; HIF, R(2) = 0.86 and RMSETe of 0.69), whereas no improvement was seen when melting point (Tm) or logDpH 6.5 were included in the models.If experimentally determined pH-dependent solubility values were available, this further improved the accuracy of the predictions.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacy, Uppsala University, Biomedical Centre, P.O. Box 580, SE-751 23, Uppsala, Sweden.

ABSTRACT

Purpose: To develop predictive models of apparent solubility (Sapp) of lipophilic drugs in fasted state simulated intestinal fluid (FaSSIF) and aspirated human intestinal fluid (HIF).

Methods: Measured Sapp values in FaSSIF, HIF and phosphate buffer pH 6.5 (PhBpH6.5) for 86 lipophilic drugs were compiled and divided into training (Tr) and test (Te) sets. Projection to latent structure (PLS) models were developed through variable selection of calculated molecular descriptors. Experimentally determined properties were included to investigate their contribution to the predictions.

Results: Modest relationships between Sapp in PhBpH6.5 and FaSSIF (R(2) = 0.61) or HIF (R(2) = 0.62) were found. As expected, there was a stronger correlation obtained between FaSSIF and HIF (R(2) = 0.78). Computational models were developed using calculated descriptors alone (FaSSIF, R(2) = 0.69 and RMSEte of 0.77; HIF, R(2) = 0.84 and RMSEte of 0.81). Accuracy improved when solubility in PhBpH6.5 was added as a descriptor (FaSSIF, R(2) = 0.76 and RMSETe of 0.65; HIF, R(2) = 0.86 and RMSETe of 0.69), whereas no improvement was seen when melting point (Tm) or logDpH 6.5 were included in the models.

Conclusion: Computational models were developed, that reliably predicted Sapp of lipophilic compounds in intestinal fluid, from molecular structures alone. If experimentally determined pH-dependent solubility values were available, this further improved the accuracy of the predictions.

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Related in: MedlinePlus

Prediction results for solubility in FaSSIF. a FaSSIF model based on seven calculated descriptors and b the same but including measured buffer solubility. Light green circles represent the training set while green and dark green circles denote the literature test set and discovery test set, respectively.
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Fig3: Prediction results for solubility in FaSSIF. a FaSSIF model based on seven calculated descriptors and b the same but including measured buffer solubility. Light green circles represent the training set while green and dark green circles denote the literature test set and discovery test set, respectively.

Mentions: The developed PLS models are summarized in Table II. The FaSSIF model (Fig. 3a) required seven calculated descriptors to produce two principal components resulting in R2 of 0.69, Q2 of 0.64 and an RMSEtr of 0.48 log10 units. The HIF model (Fig. 4a), based on nine descriptors, had a higher R2 of 0.84 (Q2 of 0.78) and a lower RMSEtr (0.34). The inclusion of experimentally determined Sapp in PhBpH6.5 strengthened the predictive power of both models to R2 of 0.76 (FaSSIF) and 0.86 for HIF (Figs. 3b and 4b, respectively), and it reduced the RMSE of the test sets (Table II). Inclusion of Tm and logDpH6.5 did not improve the developed models. Further, these properties were unable to identify over- or under-predicted compounds or any clusters.Table II


Computational prediction of drug solubility in fasted simulated and aspirated human intestinal fluid.

Fagerberg JH, Karlsson E, Ulander J, Hanisch G, Bergström CA - Pharm. Res. (2014)

Prediction results for solubility in FaSSIF. a FaSSIF model based on seven calculated descriptors and b the same but including measured buffer solubility. Light green circles represent the training set while green and dark green circles denote the literature test set and discovery test set, respectively.
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4300419&req=5

Fig3: Prediction results for solubility in FaSSIF. a FaSSIF model based on seven calculated descriptors and b the same but including measured buffer solubility. Light green circles represent the training set while green and dark green circles denote the literature test set and discovery test set, respectively.
Mentions: The developed PLS models are summarized in Table II. The FaSSIF model (Fig. 3a) required seven calculated descriptors to produce two principal components resulting in R2 of 0.69, Q2 of 0.64 and an RMSEtr of 0.48 log10 units. The HIF model (Fig. 4a), based on nine descriptors, had a higher R2 of 0.84 (Q2 of 0.78) and a lower RMSEtr (0.34). The inclusion of experimentally determined Sapp in PhBpH6.5 strengthened the predictive power of both models to R2 of 0.76 (FaSSIF) and 0.86 for HIF (Figs. 3b and 4b, respectively), and it reduced the RMSE of the test sets (Table II). Inclusion of Tm and logDpH6.5 did not improve the developed models. Further, these properties were unable to identify over- or under-predicted compounds or any clusters.Table II

Bottom Line: Modest relationships between Sapp in PhBpH6.5 and FaSSIF (R(2) = 0.61) or HIF (R(2) = 0.62) were found.Accuracy improved when solubility in PhBpH6.5 was added as a descriptor (FaSSIF, R(2) = 0.76 and RMSETe of 0.65; HIF, R(2) = 0.86 and RMSETe of 0.69), whereas no improvement was seen when melting point (Tm) or logDpH 6.5 were included in the models.If experimentally determined pH-dependent solubility values were available, this further improved the accuracy of the predictions.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacy, Uppsala University, Biomedical Centre, P.O. Box 580, SE-751 23, Uppsala, Sweden.

ABSTRACT

Purpose: To develop predictive models of apparent solubility (Sapp) of lipophilic drugs in fasted state simulated intestinal fluid (FaSSIF) and aspirated human intestinal fluid (HIF).

Methods: Measured Sapp values in FaSSIF, HIF and phosphate buffer pH 6.5 (PhBpH6.5) for 86 lipophilic drugs were compiled and divided into training (Tr) and test (Te) sets. Projection to latent structure (PLS) models were developed through variable selection of calculated molecular descriptors. Experimentally determined properties were included to investigate their contribution to the predictions.

Results: Modest relationships between Sapp in PhBpH6.5 and FaSSIF (R(2) = 0.61) or HIF (R(2) = 0.62) were found. As expected, there was a stronger correlation obtained between FaSSIF and HIF (R(2) = 0.78). Computational models were developed using calculated descriptors alone (FaSSIF, R(2) = 0.69 and RMSEte of 0.77; HIF, R(2) = 0.84 and RMSEte of 0.81). Accuracy improved when solubility in PhBpH6.5 was added as a descriptor (FaSSIF, R(2) = 0.76 and RMSETe of 0.65; HIF, R(2) = 0.86 and RMSETe of 0.69), whereas no improvement was seen when melting point (Tm) or logDpH 6.5 were included in the models.

Conclusion: Computational models were developed, that reliably predicted Sapp of lipophilic compounds in intestinal fluid, from molecular structures alone. If experimentally determined pH-dependent solubility values were available, this further improved the accuracy of the predictions.

Show MeSH
Related in: MedlinePlus