Seqens eBook - 31
SOLUBILITY
Finally, methods to predict drug absorption and bioavailability have been
5. Elder DP, Holm R. Aqueous solubility: simple predictive methods (in
improved significantly over the last decade. This includes approaches
silico, in vitro and bio-relevant approaches). Int. J Pharm. 2013;453:
which go beyond allometric scaling to the well-known Biopharmaceutical
Classification System (BCS).47 During the last few years, the BCS has been
refined into the Development Classification System (DCS),48 which addresses
3-11.
6. Gleeson MP, Hersey A, Montanari D, Overington J. Probing the links
between in vitro potency, ADMET and physicochemical parameters.
solubility, permeability, and the dose of the drug. The DCS approach also
takes into account the dissolution rate and distinguishes between solubility
and dissolution-limited absorption. The use of pharmacokinetic simulation
Nat Rev Drug Discov. 2011;10:197-208.
7. Elder DP. Effective formulation development strategies for poorly
soluble active pharmaceutical ingredients (APIs). Am Pharm Rev.
software has also become widespread49 and might allow a more detailed
2010;13(1):28-34.
understanding of the behavior of the research compound in humans and
animals, including dissolution, solubility, and an understanding of how a
8. Liu R. (Editor) Water-insoluble drug formulation. CRC Press. 2008.
drug might precipitate in the GI tract (due to shifts in physiological pH).
9. Lamanna C, Bellini M, Padova A, Westerberg G, Maccari L.
Straightforward recursive partitioning model for discarding
Conclusion
insoluble compounds in the drug discovery process. J Med Chem.
2008;51:2891-2897.
Solubility is one of the most important physicochemical parameters used
in research and development. Historically, a large number of in silico
10. Faller B., Ertl P. Computational approaches to determining drug
solubility. Adv Drug Deliv Rev. 2007;59:533-545.
solubility methods have been employed. These computational methods
provide comparative rank order assessments of solubility across different
11. Huuskonen, J. Estimation of aqueous solubility for a diverse set of
discovery programs, and they need to be able to cope with significant
organic compounds based on molecular topology. J Chem Inf Comput
numbers of compounds, with the objective of filtering out "non-druglike" compounds. Although solubility is relatively easy to define, it can
be difficult to predict using computational methods primarily due to
Sci. 2000;40:773-777.
12. Klopman G, Zhu H. Estimation of aqueous solubility of organic
compounds by the group contribution approach. J Chem Inf Comput
solid state constraints (given enthalpy and entropy considerations). The
results from the Solubility Challenge show how difficult accurate solubility
Sci. 2001;41:439-445.
prediction can be and suggest that simpler in silico methods may be
13. Tetko IV, Tanchuk VY, Kasheva TN, Villa AEP. Estimation of aqueous
more appropriate. In parallel, experimental methods to assess solubility
solubility of chemical compounds using E-state indices. J Chem Inf
Comput Sci. 2001;41:1488-1493.
have been improved and automated in recent years, and currently allow
measurement of solubility for large numbers of compounds. This holds
14. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and
especially true for the measurement of kinetic solubility. However, to
computational approaches to estimate solubility and permeability
ensure a sufficient bioavailability of drugs, thermodynamic solubility
in drug discovery and development settings. Adv Drug Deliv Rev.
becomes relevant. The use of kinetic and thermodynamic solubility should
be clearly distinguished because the erroneous use of kinetic solubility for
compound optimization can be misleading. For a deeper understanding of
2012;64:4-17.
15. Llinàs A, Glen RC, Goodman JM. Solubility challenge: can you
predict solubilities of 32 molecules using a database of 100 reliable
the role of solubility for drug absorption in animal and humans, methods
and media to mimic in vivo behavior have become more widespread and
easy to use. Finally, drug absorption can be simulated and mechanistically
measurements? J Chem Inf Model. 2008;48:1289-1303.
16. Hopfinger AJ, Esposito EX, Llinàs A, Glen RC, Goodman JM. Findings
of the challenge to predict aqueous solubility. J Chem Inf Model.
understood based on solubility data and simulation software. Therefore,
2009;49:1-5.
simulation applications are widespread.
17. Hewitt M, Cronin MTD, Enoch SJ, Madden JC, Roberts DW, Dearden
References
JC. In silico prediction of aqueous solubility: the solubility challenge. J
1. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and
computational approaches to estimate solubility and permeability
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18. Hansch C, Quinlan JE, Lawrence GL. Linear free energy relationship
between partition coefficients and the aqueous solubility of organic
in drug discovery and development settings. Adv Drug Deliv Rev.
liquids. J Org Chem. 1968;33:347-350.
1997;23:3-25.
2. Edwards MP, Price DA. Role of physicochemical properties and ligand
19. Cheng T, Li Q, Wang Y, Bryant SH. Binary classification of aqueous
lipophilicity efficiency in addressing drug safety risk. Ann Rep Med
solubility using support vector machines with reduction and
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recombinant feature selection. J Chem Inf Model. 2011;51:229-236.
3. Hopkins AL, Groom CR, Alex A. Ligand efficiency: a useful metric for
20. Kramer C, Beck B, Clark T. Insolubility classification with accurate
prediction probabilities using a metaClassifier. J Chem Inf Model.
lead selection. Drug Discovery Today. 2004;9(10):430-431.
2010;50:401-414.
4. Hill AP, Young RJ. Getting physical in drug discovery: a contemporary
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2010;15:648-655.
2006.
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Seqens eBook
Table of Contents for the Digital Edition of Seqens eBook
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