Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings (original) (raw)
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Molecular Pharmaceutics, 2012
The Biopharmaceutics Classification System (BCS) is a scientific framework that provides a basis for predicting the oral absorption of drugs. These concepts have been extended in the Biopharmaceutics Drug Disposition Classification System (BDDCS) to explain the potential mechanism of drug clearance and understand the effects of uptake and efflux transporters on absorption, distribution, metabolism, and elimination. The objective of present work is to establish criteria for provisional biopharmaceutics classification using pH-dependent passive permeability and aqueous solubility data generated from high throughput screening methodologies in drug discovery settings. The apparent permeability across monolayers of clonal cell line of Madin−Darby canine kidney cells, selected for low endogenous efflux transporter expression, was measured for a set of 105 drugs, with known BCS and BDDCS class. The permeability at apical pH 6.5 for acidic drugs and at pH 7.4 for nonacidic drugs showed a good correlation with the fraction absorbed in human (Fa). Receiver operating characteristic (ROC) curve analysis was utilized to define the permeability class boundary. At permeability ≥5 × 10 −6 cm/s, the accuracy of predicting Fa of ≥0.90 was 87%. Also, this cutoff showed more than 80% sensitivity and specificity in predicting the literature permeability classes (BCS), and the metabolism classes (BDDCS). The equilibrium solubility of a subset of 49 drugs was measured in pH 1.2 medium, pH 6.5 phosphate buffer, and in FaSSIF medium (pH 6.5). Although dose was not considered, good concordance of the measured solubility with BCS and BDDCS solubility class was achieved, when solubility at pH 1.2 was used for acidic compounds and FaSSIF solubility was used for basic, neutral, and zwitterionic compounds. Using a cutoff of 200 μg/mL, the data set suggested a 93% sensitivity and 86% specificity in predicting both the BCS and BDDCS solubility classes. In conclusion, this study identified pH-dependent permeability and solubility criteria that can be used to assign provisional biopharmaceutics class at early stage of the drug discovery process. Additionally, such a classification system will enable discovery scientists to assess the potential limiting factors to oral absorption, as well as help predict the drug disposition mechanisms and potential drug−drug interactions.
Analytical and Bioanalytical Chemistry, 2009
The measurement of physicochemical properties at an early phase of drug discovery and development is crucial to reduce attrition rates due to poor biopharmaceutical properties. Among these properties, ionization, lipophilicity, solubility and permeability are mandatory to predict the pharmacokinetic behavior of NCEs (new chemical entities). Due to the high number of NCEs, the analytical tools used to measure these properties are automated and progressively adapted to high-throughput technologies. The present review is dedicated to experimental methods applied in the early drug discovery process for the determination of solubility, ionization constants, lipophilicity and permeability of small molecules. The principles and experimental conditions of the different methods are described, and important enhancements in terms of throughput are highlighted.
Experimental and computational screening models for prediction of aqueous drug solubility
Pharmaceutical Research, 2002
To devise experimental and computational models to predict aqueous drug solubility. Methods. A simple and reliable modification of the shake flask method to a small-scale format was devised, and the intrinsic solubilities of 17 structurally diverse drugs were determined. The experimental solubility data were used to investigate the accuracy of commonly used theoretical and semiexperimental models for prediction of aqueous drug solubility. Computational models for prediction of intrinsic solubility, based on lipophilicity and molecular surface areas, were developed. Results. The intrinsic solubilities ranged from 0.7 ng/mL to 6.0 mg/ mL, covering a range of almost seven log 10 units, and the values determined with the new small-scale shake flask method agreed well with published solubility data. Solubility data computed with established theoretical models agreed poorly with the experimentally determined solubilities, but the correlations improved when experimentally determined melting points were included in the models. A new, fast computational model based on lipophilicity and partitioned molecular surface areas, which predicted intrinsic drug solubility with a good accuracy (R 2 of 0.91 and RMSE tr of 0.61) was devised.
Development of Reliable Aqueous Solubility Models and Their Application in Druglike Analysis
Journal of Chemical Information and Modeling, 2007
In this work, two reliable aqueous solubility models, ASMS (aqueous solubility based on molecular surface) and ASMS-LOGP (aqueous solubility based on molecular surface using ClogP as a descriptor), were constructed by using atom type classified solvent accessible surface areas and several molecular descriptors for a diverse data set of 1708 molecules. For ASMS (without using ClogP as a descriptor), the leave-oneout q 2 and root-mean-square error (RMSE) were 0.872 and 0.748 log unit, respectively. ASMS-LOGP was slightly better than ASMS (q 2) 0.886, RMSE) 0.705). Both models were extensively validated by three cross-validation tests and encouraging predictability was achieved. High throughput aqueous solubility prediction was conducted for a number of data sets extracted from several widely used databases. We found that real drugs are about 20-fold more soluble than the so-called druglike molecules in the ZINC database, which have no violation of Lipinski's "Rule of 5" at all. Specifically, oral drugs are about 16-fold more soluble, while injection drugs are 50-60-fold more soluble. If the criterion of a molecule to be soluble is set to-5 log unit, about 85% of real drugs are predicted as soluble; in contrast only 50% of druglike molecules in ZINC are soluble. We concluded that the two models could be served as a rule in druglike analysis and an efficient filter in prioritizing compound libraries prior to high throughput screenings (HTS).
Calculation of drug-like molecules solubility using predictive activity coefficient models
Fluid Phase Equilibria, 2012
The A-UNIFAC, UNIFAC, and NRTL-SAC models are used to predict solubility in pure solvents of a set of drug-like molecules. To apply A-UNIFAC, a new set of residual interaction parameters between the ACOH group and six other groups had to be estimated. The solute model parameters of NRTL-SAC were also estimated for this set of molecules. NRTL-SAC showed better performance at 298.15 K, with an average absolute deviation of 37.6%. Solubility dependence with temperature was also studied: all models presented average deviations around 40%. In general, there is an improvement given by the A-UNIFAC over the UNIFAC in aqueous systems, proving the importance of taking association into account.
Journal of Pharmaceutical Sciences, 1993
A modification of the extended Hansen method is used for estimating the solubility of sulfadiazine and other organic drug molecules in a number of individual solvents ranging from nonpolar to highly polar. The equations obtained for each drug involve the partial solubility parameters of the solvents and allow the prediction of solubility of these drugs in a new solvent. Furthermore, a number of drugs (e.g., sulfadiazine, sulfamethoxypyridazine, naphthalene, and some benzoic acid derivatives) are combined in a single expression including the ideal solubility of the drugs and the partial solubility parameters of the solvents. The equation fits the solubilities of these drugs in a wide variety of solvents and may be used to predict the solubility of other sulfonamides and benzoic acid derivatives in semipolar and highly polar solvents. The solvatochromic parameter approach is also used in models for predicting the solubility of single drugs in individual solvents. It was tested with multiple solutes as was the partial solubility parameter approach. However, the latter approach is superior; the parameters of the solubility parameter method are all statistically significant for drugs tested individually or together in a single equation, a condition that is not obtained with the solvatochromic model.
The drug-in-rat permeability rate coefficient for thirteen types was examined. As drug or drug-like molecules are, in general, complex structures of amphiphilic nature, (i.e., having both hydrophobic and hydrophilic moieties), the permeation rate was expressed as a function of some selected molecular descriptors; namely, the Ghose-Crippen octanol-water partition coefficient, ALOGP; the hydrophilicity, Hy; the mean topological charge index of order 1, JGI1; the mean topological charge index of order 2, JGI2; the mean atomic polarizability (scaled on carbon atom), Mp; the mean electro-topological state, Ms; the mean atomic van der Waals volume (scaled on carbon atom), Mv; the number of rotatable bonds, RBN; the number of acceptor atoms for H-bonds (N,O,F), nHAcc; the number of donor atoms for H-bonds (N and O), nHDon; and finally the Kier flexibility index, PHI. Using the nonlinear regression approach, it was found that the drug-in-rat permeability rate data can be adequately and sati...