This research examined the applicability of using a neural network approach to the estimation of aqueous activity coefficients of aromatic organic compounds from fragmented structural information. A set of 95 compounds was used to train the neural network, and the trained network was tested on a set of 31 compounds. A comparison was made between the results and those obtained using multiple linear regression analysis. With the proper selection of neural network parameters, the backpropagation network provided a more accurate prediction of the aqueous activity coefficients for testing data than did regression analysis. This research indicates that neural networks have the potential to become a useful analytical technique for quantitative prediction of structure-activity relationships.

Hydrocarbons↗

PubMedDate not supplied

Prediction of drug solubility by the general solubility equation (GSE).

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 (K(ow)). 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.

Pharmaceutical Preparations↗

PubMedDate not supplied

Prediction of aqueous solubility of organic compounds by the general solubility equation (GSE).

The revised general solubility equation (GSE) is used along with four different methods including Huuskonen's artificial neural network (ANN) and three multiple linear regression (MLR) methods to estimate the aqueous solubility of a test set of the 21 pharmaceutically and environmentally interesting compounds. For the selected test sets, it is clear that the GSE and ANN predictions are more accurate than MLR methods. The GSE has the advantages of being simple and thermodynamically sound. The only two inputs used in the GSE are the Celsius melting point (MP) and the octanol water partition coefficient (K(ow)). No fitted parameters and no training data are used in the GSE, whereas other methods utilize a large number of parameters and require a training set. The GSE is also applied to a test set of 413 organic nonelectrolytes that were studied by Huuskonen. Although the GSE uses only two parameters and no training set, its average absolute errors is only 0.1 log units larger than that of the ANN, which requires many parameters and a large training set. The average absolute error AAE is 0.54 log units using the GSE and 0.43 log units using Huuskonen's ANN modeling. This study provides evidence for the GSE being a convenient and reliable method to predict aqueous solubilities of organic compounds.

Journal Article↗

PubMedDate not supplied

Comparison of two methods for predicting aqueous solubility.

This study compares the solubility predictions of the two parameter general solubility equation (GSE) of Jain and Yalkowsky with the 171 parameter Klopman group contribution approach. Melting points and partition coefficients were obtained for each of the compounds from Klopman's test set. Using these two variables, the solubility of each compound was calculated by the GSE and compared to the values predicted by Klopman. Both methods give reasonable solubility predictions. The data of Klopman produced an average absolute error (AAE) of 0.71 and a root-mean-square error (RMSE) of 0.86, while the GSE had an AAE of 0.64 and a RMSE of 0.92.

Journal Article↗

PubMedDate not supplied

Evaluation of intravenous flavopiridol formulations.

Flavopiridol is currently under consideration as a parenteral treatment of breast tumors. The solubility of this poorly water-soluble compound can be increased by a number of methods. However, because of its low water solubility, precipitation of the solubilized drug upon injection can be a problem. The potential of several flavopiridol formulations to precipitate is evaluated using a static serial dilution technique. It is shown that formulations containing up to 10 mg/mL of flavopiridol which produce negligible precipitation on dilution can be developed.

Antineoplastic Agents↗

PubMedDate not supplied

The role of the effective concentration in interpreting hemolysis data.

Problems inherent in traditional methods of determining the hemolytic activity of parenteral compounds are discussed. Data taken from a study which closely models the conditions present for an intravenous injection are re-examined. An equation is given which combines several variables into a single parameter, the effective concentration. A strong relationship is found between the effective concentration of the compound of interest and the hemolysis produced.

Dose-Response Relationship, Drug↗

PubMedDate not supplied

Acceleration of heat transfer in vial freeze-drying of pharmaceuticals. I: Corrugated aluminum quilt.

The medium offering the greatest resistance to heat transfer from the freeze-dryer shelf to the moving and subliming interface within the product is the space between the flat shelf top and the concave vial bottom. The resistance to heat transfer can be greatly reduced by improving the thermal conductivity of this intervening space. Several heat transfer augmentation devices, which fill this gap, are described. The devices are inexpensive and easy to use. Experimental data show that the resistance of the intervening space is reduced appreciably and the drying time is greatly reduced.

Aluminum↗

PubMedDate not supplied