[Free Download E-Book] Handbook of Solubility Data for Pharmaceuticals
15:40Handbook of Solubility Data for Pharmaceuticals | Abolghasem Jouyban
Introduction
Before a drug becomes available to its receptors, it should be
dissolved in the biological fluids surrounding the receptors; therefore,
solubility is an important subject in pharmaceutical sciences. There is a
solubility problem with nearly 40% of the drug candidates, and any attempt to
predict the solubility is quite important in drug discovery investigations. The
oldest rule for solubility prediction is “like dissolves like.” This rule is
applied to a well-known solubility equation, i.e., the Hildebrand equation, in which
the solubility of a solute reaches the maximum value when the Hildebrand
solubility parameters of the solute and solvent are equal. However, it has been
shown that the Hildebrand equation is valid only for solutions with nonspecifc
interactions. Water is the unique biological solvent and aqueous solubility is
one of the most important physicochemical properties (PCPs) of drugs; it is
therefore obvious that simple equations like the Hildebrand equation cannot
represent the aqueous solubility of solutes consisting of various functional
groups, such as pharmaceuticals. More accurate equations are needed to predict
the aqueous solubility of drugs, which will be discussed in detail later on.
Aqueous solubility is also a key factor in the design of oral, parenteral, and
ophthalmic formulations of poorly water-soluble drugs. A comprehensive database
of aqueous solubilities of chemicals and pharmaceuticals was collected by
Yalkowsky and He. Solubility is defined as the maximum quantity of a drug
dissolved in a given volume of a solvent/ solution. For ionizable drugs, the
solubility could be affected by the pH of the solution, and the intrinsic
solubility (S0) is defned as the concentration of a saturated solution of the
neutral form of the drug in equilibrium with its solid. The United States
Pharmacopeia classifed the solubilities of drugs into seven classes. Aqueous
solubility has an essential role in the bioavailability of oral drug
formulations. There is an established classifcation, namely, the biopharmaceutical
classifcation system (BCS), which divides drugs into four classes in terms of
their solubility and permeability. The BCS classifcation correlates the in
vitro solubility and permeability to the in vivo bioavailability. Soluble and
permeable drugs are class I drugs with oral bioavailability being limited by
their ability to reach the absorption sites. Class II drugs are poorly soluble
but permeable drugs through the gastrointestinal tract (GI), meaning that their
oral absorption is limited by the drug’s solubility and, as a consequence of
the Noyes–Whitney equation, by their dissolution rate. Class III drugs are
soluble but poorly permeable and their oral bioavailability is limited by the
barrier properties of the GI tract. Drugs of class IV are low soluble and
poorly permeable compounds with the limitations of classes II and III. The drug
candidates of class I possess suitable bioavailabilities and show appropriate
drugability potentials; the bioavailability of drug candidates of class II can
potentially be improved by developing suitable formulation designs, while those
that belong to classes III and IV are most likely to return to the lead
optimization phase for the improvement of their PCP.
Contents
Chapter
1 Introduction
1.1
Solubility Determination Methods
1.1.1
Shake-Flask Method
1.1.2
Kinetic Solubility Determination
1.2
Aqueous Solubility Prediction Methods
1.3
Solubility Prediction in Organic Solvents
1.4 The
Accuracy Criteria in Solubility Calculation Methods
1.5
Acceptable MPD Range in Solubility Calculations
1.6
Solubilization of Drugs by Cosolvency
1.7
Review of Cosolvency Models
1.7.1
Hildebrand Solubility Approach
1.7.2
Solubility–Dielectric Constant Relationship Model
1.7.3
Log-Linear Model of Yalkowsky
1.7.4
Extended Hildebrand Solubility Approach
1.7.5
Williams–Amidon Model
1.7.6
Mixture Response Surface Model
1.7.7
Khossravi–Connors Model
1.7.8
Jouyban–Acree Model
1.7.9
Modifed Wilson Model
1.7.10
Margules Equation
1.7.11
General Single Model
1.7.12
Mobile Order and Disorder Theory
1.7.13
QSPR Model of Rytting
1.7.14
Artifcial Neural Network Model
1.7.15
COSMO-RS Model
1.7.16
New Models Proposed by Yalkowsky’s Group
1.8
Concluding Remarks
References
Chapter
2 Solubility Data in Organic Solvents
References
Chapter
3 Solubility Data in Binary Solvent Mixtures
References
Chapter
4 Solubility Data in Ternary Solvent Mixtures
References
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