The Experts below are selected from a list of 43122 Experts worldwide ranked by ideXlab platform
Christel A S Bergstrom - One of the best experts on this subject based on the ideXlab platform.
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molecular simulation as a computational pharmaceutics tool to predict Drug Solubility solubilization processes and partitioning
European Journal of Pharmaceutics and Biopharmaceutics, 2019Co-Authors: Shakhawath Hossain, Christel A S Bergstrom, Aleksei Kabedev, Albin Parrow, Per LarssonAbstract:In this review we will discuss how computational methods, and in particular classical molecular dynamics simulations, can be used to calculate Solubility of pharmaceutically relevant molecules and ...
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computational prediction of Drug Solubility in fasted simulated and aspirated human intestinal fluid
Pharmaceutical Research, 2015Co-Authors: Jonas H Fagerberg, Eva Karlsson, Johan Ulander, Gunilla Hanisch, Christel A S BergstromAbstract: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).
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computational prediction of Drug Solubility in lipid based formulation excipients
Pharmaceutical Research, 2013Co-Authors: Linda C Persson, Christel A S Bergstrom, Christopher J H Porter, William N CharmanAbstract:Purpose To investigate if Drug Solubility in pharmaceutical excipients used in lipid based formulations (LBFs) can be predicted from physicochemical properties.
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computational models to predict aqueous Drug Solubility permeability and intestinal absorption
Expert Opinion on Drug Metabolism & Toxicology, 2005Co-Authors: Christel A S BergstromAbstract:In the last decade, poor intestinal absorption of candidate Drugs intended for oral administration has been identified as a major bottleneck in Drug development. Poor intestinal absorption can often be related to poor aqueous Solubility and/or poor permeability across the intestinal wall. Other factors, such as poor stability and the metabolism of the compounds, can also decrease the amount of compound absorbed. In an effort to design compounds with enhanced absorption profile, theoretical predictions of Solubility and permeability, among other factors, have gained increased interest, and a large number of papers have been published. In this review, the databases and techniques used for the development of in silico absorption models will be discussed. The focus is on aqueous Drug Solubility, which has become a major problem in Drug development.
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x ray yield and selectively excited x ray emission spectra of atenolol and nadolol
Journal of Electron Spectroscopy and Related Phenomena, 2005Co-Authors: Johan Soderstrom, Christel A S Bergstrom, Johan Grasjo, Stepan Kashtanov, Marcus Agaker, T Schmitt, Andreas Augustsson, Laurent Duda, Jinghua Guo, J NordgrenAbstract:A pre-study in a project aimed at increasing the understanding of Drug Solubility by applying X-ray spectroscopy to substances in solid phases, in aqueous solution, and in gas-phase is presented. Influence of the molecular surrounding on the local electronic structure is reflected in X-ray yield fine structure, and in site-selectively excited X-ray emission spectra. Results for atenolol and nadolol in solid form are discussed.
Per Artursson - One of the best experts on this subject based on the ideXlab platform.
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accuracy of calculated ph dependent aqueous Drug Solubility
European Journal of Pharmaceutical Sciences, 2004Co-Authors: Christel A S Bergstrom, Kristina Luthman, Per ArturssonAbstract:New effective experimental techniques in medicinal chemistry and pharmacology have resulted in a vast increase in the number of pharmacologically interesting compounds. However, the number of new Drugs undergoing clinical trial has not augmented at the same pace, which in part has been attributed to poor absorption of the compounds.The main objective of this thesis was to investigate whether computer-based models devised from calculated molecular descriptors can be used to predict aqueous Drug Solubility, an important property influencing the absorption process. For this purpose, both experimental and computational studies were performed. A new small-scale shake flask method for experimental Solubility determination of crystalline compounds was devised. This method was used to experimentally determine Solubility values used for the computational model development and to investigate the pH-dependent Solubility of Drugs. In the computer-based studies, rapidly calculated molecular descriptors were used to predict aqueous Solubility and the melting point, a solid state characteristic of importance for the Solubility. To predict the absorption process, Drug permeability across the intestinal epithelium was also modeled.The results show that high quality Solubility data of crystalline compounds can be obtained by the small-scale shake flask method in a microtiter plate format. The experimentally determined pH-dependent Solubility profiles deviated largely from the profiles predicted by a traditionally used relationship, highlighting the risk of data extrapolation. The in silico Solubility models identified the non-polar surface area and partitioned total surface areas as potential new molecular descriptors for Solubility. General Solubility models of high accuracy were obtained when combining the surface area descriptors with descriptors for electron distribution, connectivity, flexibility and polarity. The used descriptors proved to be related to the solvation of the molecule rather than to solid state properties. The surface area descriptors were also valid for permeability predictions, and the use of the Solubility and permeability models in concert resulted in an excellent theoretical absorption classification. To summarize, the experimental and computational models devised in this thesis are improved absorption screening tools applicable to the lead optimization in the Drug discovery process.
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global and local computational models for aqueous Solubility prediction of Drug like molecules
Journal of Chemical Information and Computer Sciences, 2004Co-Authors: Christel A S Bergstrom, Ulf Norinder, Kristina Luthman, Carola M Wassvik, Per ArturssonAbstract:The aim of this study was to develop in silico protocols for the prediction of aqueous Drug Solubility. For this purpose, high quality Solubility data of 85 Drug-like compounds covering the total Drug-like space as identified with the ChemGPS methodology were used. Two-dimensional molecular descriptors describing electron distribution, lipophilicity, flexibility, and size were calculated by Molconn-Z and Selma. Global minimum energy conformers were obtained by Monte Carlo simulations in MacroModel and three-dimensional descriptors of molecular surface area properties were calculated by Marea. PLS models were obtained by use of training and test sets. Both a global Drug Solubility model (R(2) = 0.80, RMSE(te) = 0.83) and subset specific models (after dividing the 85 compounds into acids, bases, ampholytes, and nonproteolytes) were generated. Furthermore, the final models were successful in predicting the Solubility values of external test sets taken from the literature. The results showed that homologous series and subsets can be predicted with high accuracy from easily comprehensible models, whereas consensus modeling might be needed to predict the aqueous Drug Solubility of datasets with large structural diversity.
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experimental and computational screening models for prediction of aqueous Drug Solubility
Pharmaceutical Research, 2002Co-Authors: Christel A S Bergstrom, Ulf Norinder, Kristina Luthman, Per ArturssonAbstract:Purpose. 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 log10 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 2of 0.91 and RMSEtr of 0.61) was devised. Conclusions. A small-scale shake flask method for determination of intrinsic Drug Solubility was developed, and a promising alternative computational model for the theoretical prediction of aqueous Drug Solubility was proposed.
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experimental and computational screening models for prediction of aqueous Drug Solubility
Pharmaceutical Research, 2002Co-Authors: Christel A S Bergstrom, Ulf Norinder, Kristina Luthman, Per ArturssonAbstract:Purpose. To devise experimental and computational models to predict aqueous Drug Solubility.
Samuel H. Yalkowsky - One of the best experts on this subject based on the ideXlab platform.
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overcoming the challenges of low Drug Solubility in the intravenous formulation of solithromycin
Journal of Pharmaceutical Sciences, 2018Co-Authors: Daniel Evans, Samuel H. Yalkowsky, David Pereira, Prabha FernandesAbstract:Abstract Solithromycin is a fluoro-ketolide (a fourth-generation macrolide) antibiotic that has been undergoing clinical trials for the treatment of community-acquired bacterial pneumonia. In this study, development of the tri-amino acid–buffered solithromycin intravenous (IV) formulation was performed to minimize the occurrence of infusion-associated local adverse events (infusion-site pain or phlebitis) observed in patients who received the tartaric acid–buffered IV formulation with a lower buffered capacity during phase I clinical trials. Development of the tri-amino acids–buffered solithromycin IV formulation was achieved using a dynamic in vitro precipitation model. Computational modeling also supports the superiority of the amino acid-buffered formulation over the tartaric aid–buffered formulation.
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stacking complexation by nicotinamide a useful way of enhancing Drug Solubility
International Journal of Pharmaceutics, 2007Co-Authors: Ritesh Sanghvi, Daniel Evans, Samuel H. YalkowskyAbstract:The Solubility enhancement of 11 poorly soluble Drugs by complexation using nicotinamide has been studied. The solubilization efficiency of nicotinamide has been compared to that of hydroxypropyl-β-cyclodextrin and sulfobutylether-β-cyclodextrin. Solubility enhancements as high as 4000-fold are observed in 20% (w/v) nicotinamide solution. Furthermore, nicotinamide is more effective than cyclodextrins for solubilizing some of the Drugs. The mechanism of Drug solubilization by nicotinamide is investigated by studying the effects of nicotinamide concentration on the surface tension and the conductivity of water. A slight break in both, the surface tension and conductivity is noticed at around 10% (w/v), suggesting self-association at higher concentrations. Corresponding breaks in the Solubility profiles of estrone and griseofulvin at similar concentrations support self-association. Based on this observation it appears that at low concentrations, one molecule of nicotinamide undergoes complexation with one Drug molecule to form a 1:1 complex. At higher concentrations, two molecules of nicotinamide undergo complexation with one Drug molecule forming a 1:2 complex. The complexation constants have been calculated for all the Drugs and the data are well described by this model. Expectedly, increasing the temperature reduces the complexation constants.
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comparison of the octanol water partition coefficients calculated by clogp acdlogp and kowwin to experimentally determined values
International Journal of Pharmaceutics, 2005Co-Authors: Stephen G Machatha, Samuel H. YalkowskyAbstract:The experimental octanol/water partition coefficient data, of 108 compounds from the data set [Rytting, E., Lentz, K.A., Chen, X., Qian, F., Venkatesh, S., 2004. A quantitative structure-property relationship for predicting Drug Solubility in PEG 400/water cosolvent systems. Pharm. Res. 21, 237-244] was compared to calculated values using the computer programs ClogP, ACD/logPdb and KowWin. It was found that all the three programs have a user friendly interface but ClogP appears to be the more accurate predictor of log K(ow).
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solubilization and preformulation of carbendazim
International Journal of Pharmaceutics, 2002Co-Authors: Nina Ni, Tapan Sanghvi, Samuel H. YalkowskyAbstract:Abstract The solubilization of carbendazim by pH in combination with cosolvents, surfactants or complexants was investigated. At pH 7 the total Drug Solubility is 6.11±0.45 μg/ml which increases by 1–7 fold with cosolvent, surfactant or complexant. However, at pH 2 the Solubility increases by 250 times. Cosolvents have a negligible effect (50% increase) on the total Drug Solubility at pH 2 because of the high polarity of the cationic Drug. Also pH combined with nonionic surfactants does not improve Solubility, as relatively less polar micelles are not able to accommodate the cationic Drug. Interestingly, the total Drug Solubility increases by combining pH 2 with complexants, as they can form a complex with the isolated aromatic ring of both the unionized and the ionized Drug. The proposed oral formulation of 1 mg/ml carbendazim at pH 2 does not precipitate in the presence of Seven Up or water. But it does precipitate with pH 7 buffer when diluted 1:10 but not 1:100 or 1:250.
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prediction of Drug Solubility by the general Solubility equation gse
Journal of Chemical Information and Computer Sciences, 2001Co-Authors: Samuel H. YalkowskyAbstract:The revised general Solubility equation (GSE) proposed by Jain and Yalkowsky is used to estimate the aqueous Solubility of a set of organic nonelectrolytes studied by Jorgensen and Duffy. The only inputs used in the GSE are the Celsius melting point (MP) and the octanol water partition coefficient (Kow). These are generally known, easily measured, or easily calculated. The GSE does not utilize any fitted parameters. The average absolute error for the 150 compounds is 0.43 compared to 0.56 with Jorgensen and Duffy's computational method, which utilitizes five fitted parameters. Thus, the revised GSE is simpler and provides a more accurate estimation of aqueous Solubility of the same set of organic compounds. It is also more accurate than the original version of the GSE.
Peter A Crafts - One of the best experts on this subject based on the ideXlab platform.
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correlation and prediction of Drug molecule Solubility in mixed solvent systems with the nonrandom two liquid segment activity coefficient nrtl sac model
Industrial & Engineering Chemistry Research, 2006Co-Authors: Chau-chyun Chen, Peter A CraftsAbstract:The recently developed Nonrandom Two-Liquid Segment Activity Coefficient (NRTL−SAC) model [reported by Chen and Song, Ind. Eng. Chem. Res. 2004, 43, 8354] offers a practical thermodynamic framework to predict Drug Solubility in a wide range of solvents, based on a small initial set of measured Solubility data. The model yields satisfactory results in first correlating Drug Solubility in a few representative pure solvents and then qualitatively predicting Drug Solubility in other pure solvents. Here, we investigate the applicability of the NRTL−SAC model for predicting Drug Solubility in mixed solvents for three molecules: acetaminophen, sulfadiazine, and cimetidine. The study shows that the model provides robust correlation and prediction of Drug Solubility in both pure and mixed solvents, with a qualitative level of accuracy. The model is a useful tool in support of the early stages of crystallization process development and other areas of Drug process design.
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correlation and prediction of Drug molecule Solubility in mixed solvent systems with the nonrandom two liquid segment activity coefficient nrtl sac model
Industrial & Engineering Chemistry Research, 2006Co-Authors: Chau-chyun Chen, Peter A CraftsAbstract:The recently developed Nonrandom Two-Liquid Segment Activity Coefficient (NRTL−SAC) model [reported by Chen and Song, Ind. Eng. Chem. Res. 2004, 43, 8354] offers a practical thermodynamic framework to predict Drug Solubility in a wide range of solvents, based on a small initial set of measured Solubility data. The model yields satisfactory results in first correlating Drug Solubility in a few representative pure solvents and then qualitatively predicting Drug Solubility in other pure solvents. Here, we investigate the applicability of the NRTL−SAC model for predicting Drug Solubility in mixed solvents for three molecules: acetaminophen, sulfadiazine, and cimetidine. The study shows that the model provides robust correlation and prediction of Drug Solubility in both pure and mixed solvents, with a qualitative level of accuracy. The model is a useful tool in support of the early stages of crystallization process development and other areas of Drug process design.
Abolghasem Jouyban - One of the best experts on this subject based on the ideXlab platform.
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experimental and computational methods pertaining to Drug Solubility
2012Co-Authors: Abolghasem Jouyban, Mohammad Amin Abolghassemi FakhreeAbstract:Solubility of a Drug is one of its important physico-chemical properties. More attention has been paid to the aqueous Solubility since water is the unique solvent of biological systems. It is obvious that a Drug should be reached to its receptors in the body through the aqueous and non-aqueous media. The chance of a low water soluble Drug to be appeared in the market place is very low and nearly 40 % of the Drug candidates fail to reach higher phases of the Drug trials simply because of their low water Solubility. The Solubility in non-aqueous solvents is not too important from clinical viewpoint however these solubilities play curious roles in Drug discovery and development investigations. Most of Drugs are synthesized in non-aqueous media and/or extracted from natural sources using non-aqueous extracting solvents. Different polymorphs of some Drugs could be produced from their crystallization using organic solvents. There are various methods for Solubility determination of Drugs which is discussed in this chapter. The experimental determination is tedious and time-consuming process and sometimes there is restrictions in the availability of enough amount of a Drug candidate to be used in the Solubility measurements, especially in the early stages of Drug discovery investigations in which only small amount of a Drug is synthesized/extracted and large number of preliminary biological tests should be carried out. To cover this limitation, and in order to provide a faster and easier tool, mathematical models have been developed to correlate/predict the Solubility of Drugs. These models are discussed in this chapter to provide an overall view for a pharmaceutical scientist who is working in the research and development department of a company and/or a research laboratory within academia. In addition to the accurate calculations which are expected from these models, the simplicity of the required computations is another parameter which should be taken into account, since more complex computations did not attract more attention in the pharmaceutical industry.
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prediction of Drug Solubility in mixed solvents using computed abraham parameters
Journal of Molecular Liquids, 2009Co-Authors: Abolghasem Jouyban, Mohammad Amin Abolghassemi Fakhree, Shahla Soltanpour, Elnaz Tamizi, Somaieh Soltani, William Eugence AcreeAbstract:Abstract Solubilization of Drugs/Drug candidates is still a challenging area in Drug discovery and development investigations which computational methods could play a significant role in solving the problem. An extended version of the Jouyban-Acree model using computational Abraham's solute parameters was proposed to compute the Solubility of Drugs in aqueous mixtures of the cosolvents. A generally trained version of the combined model was proposed which is able to predict the Solubility of Drugs in water–cosolvent mixtures at various temperatures using the Solubility data in neat cosolvent and water as experimental input values. The overall mean percentage deviation was 42.4 ± 59.5% which was significantly less than the overall mean percentage deviation of the similar one, i.e. log–linear model, 77.7 ± 80.8%. More general and accurate models were provided for predicting the Drug Solubility in water–cosolvent mixtures at various temperatures which could be employed in early stages of Drug discovery and development processes to find the most appropriate cosolvent and its best composition for solubilizing a desired amount of the Drug/Drug candidate in a given volume of the solution.
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prediction of Drug Solubility in water propylene glycol mixtures using jouyban acree model
Die Pharmazie, 2007Co-Authors: Abolghasem JouybanAbstract:A trained version of the Jouyban-Acree model was presented to predict Drug Solubility in water-propylene glycol mixtures at various temperatures. The model is able to predict the Solubility in various Solubility units and requires the experimental Solubility of a solute in mono-solvent systems. The mean percentage deviation (MPD) of predicted solubilities was computed to show the accuracy of the predicted data and 24% was found as the average MPD for 27 data sets studied. The proposed model enables the researchers to predict solubiliy in water-propylene glycol mixtures at various temperatures and reduces the number of required experimental data from five to two points.
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in silico prediction of Drug Solubility in water ethanol mixtures using jouyban acree model
Journal of Pharmacy and Pharmaceutical Sciences, 2006Co-Authors: Abolghasem Jouyban, William E AcreeAbstract:Article on the in silico prediction of Drug Solubility in water-ethanol mixtures using Jouyban-Acree model.
