Manish Grover - Academia.edu (original) (raw)

Papers by Manish Grover

Research paper thumbnail of Disodium pamidronate formulation

Research paper thumbnail of Solid oral pharmaceutical compositions of telmisartan, essentially free of surfactants

Research paper thumbnail of Pharmaceutical composition comprising a combination of eperisone and diclofenac and process for preparing thereof

Research paper thumbnail of Computer-Aided Instruction in Pharmaceutical Education: Retrospect and Prospects

Research paper thumbnail of In Silico ADME Predictions using Quantitative Structure Pharmacokinetic Relationships. Part II: Descriptors

Research paper thumbnail of Stability-indicating analysis of isoxazolyl penicillins using dual wavelength high-performance liquid chromatography

Journal of chromatography. B, Biomedical sciences and applications, Jan 24, 1998

Stability-indicating high-performance liquid chromatography analytical procedures were developed ... more Stability-indicating high-performance liquid chromatography analytical procedures were developed for specific determination of four isoxazolyl penicillins during degradation under neutral and accelerated acid/alkali conditions. The chromatographic conditions were set so that the drug peak was well separated from the peaks of the degradation products. Peak homogeneity of the resolving drug peak was assessed by the shape of the ratio chromatogram. Good and reproducible separations were achieved on a reversed-phase column using a mobile phase consisting of acetonitrile and a solution of 20 mM potassium dihydrogen phosphate plus 10 mM tetramethylammonium chloride in water (adjusted to pH 5). Optimal separations for all four drugs were achieved within the range of 15-21% organic modifier in the mobile phase. The detection wavelengths were 220 nm and 240 nm. The stability-indicating nature of the methods was confirmed by the linearity of the pseudo-first order plots. The utility of dual-w...

Research paper thumbnail of Correlation of Penicillin Structure with Rate Constants for Basic Hydrolysis

Pharmacy and Pharmacology Communications, 2000

The rates of degradation of 16 different penicillins have been determined at 35 C in borate buffe... more The rates of degradation of 16 different penicillins have been determined at 35 C in borate buffer, pH 9Á2, by use of stability-indicating HPLC assay procedures. The best-®t was sought between pseudo ®rst-order hydrolytic rate constants and different types of structural descriptor. Constitutional, topological, geometric and electrostatic descriptors were calculated using WHIM-3D=QSAR and CODESSA software. Advanced semi-empirical and ab-initio calculations were performed using AMPAC software. CODESSA was used to develop (multi)linear correlation models, perform cluster analysis of the experimental data and molecular descriptors, and interpret the developed models. The best correlations with the rates of hydrolysis of the drugs were found for topological, electrostatic and quantumchemical descriptors.

Research paper thumbnail of Quantitative structure–property relationships in pharmaceutical research – Part 1

Pharmaceutical Science & Technology Today, 2000

Quantitative structure-property relationship (QSPR) studies based on artificial neural network (A... more Quantitative structure-property relationship (QSPR) studies based on artificial neural network (ANN) and wavelet neural network (WNN) techniques were carried out for the prediction of solvent polarity. Experimental S′ values for 69 solvents were assembled. This set included saturated and unsaturated hydrocarbons, solvents containing halogen, cyano, nitro, amide, sulfide, mercapto, sulfone, phosphate, ester, ether, etc. Semi-empirical quantum chemical calculations at AM1 level were used to find the optimum 3D geometry of the studied molecules and different quantum-chemical descriptors were calculated by the HyperChem software. A stepwise MLR method was used to select the best descriptors and the selected descriptors were used as input neurons in neural network models. The results obtained by the two methods were compared and it was shown that in WNN, the convergence speed was faster and the root mean square error of prediction set was also smaller than ANN. The average relative error in WNN was 7.9 and 6.8% for calibration and prediction set, respectively, and the results showed the ability of the WNN developed here to predict solvent polarity.

Research paper thumbnail of Quantitative structure–property relationships in pharmaceutical research – Part 2

Pharmaceutical Science & Technology Today, 2000

Quantitative structure-property relationship (QSPR) studies based on artificial neural network (A... more Quantitative structure-property relationship (QSPR) studies based on artificial neural network (ANN) and wavelet neural network (WNN) techniques were carried out for the prediction of solvent polarity. Experimental S′ values for 69 solvents were assembled. This set included saturated and unsaturated hydrocarbons, solvents containing halogen, cyano, nitro, amide, sulfide, mercapto, sulfone, phosphate, ester, ether, etc. Semi-empirical quantum chemical calculations at AM1 level were used to find the optimum 3D geometry of the studied molecules and different quantum-chemical descriptors were calculated by the HyperChem software. A stepwise MLR method was used to select the best descriptors and the selected descriptors were used as input neurons in neural network models. The results obtained by the two methods were compared and it was shown that in WNN, the convergence speed was faster and the root mean square error of prediction set was also smaller than ANN. The average relative error in WNN was 7.9 and 6.8% for calibration and prediction set, respectively, and the results showed the ability of the WNN developed here to predict solvent polarity.

Research paper thumbnail of Lipophilic drug derivatives in liposomes

International Journal of Pharmaceutics, 1998

The drug molecules can be classified into four categories, ie highly hydrophilic, highly lipophil... more The drug molecules can be classified into four categories, ie highly hydrophilic, highly lipophilic, amphiphilic and those with biphasic insolubility. These are located differently in the liposomes and exhibit different entrapment and release behaviour. Problems like poor ...

Research paper thumbnail of RP-HPLC Determination of Lipophilicity of 22 Penicillins, Their Correlation with Reported Values and Establishment of Quantitative Structure-log Kw Relationships

QSAR & Combinatorial Science, 2005

ABSTRACT Lipophilicity parameters were determined for a series of 22 penicillins by the reversed ... more ABSTRACT Lipophilicity parameters were determined for a series of 22 penicillins by the reversed phase high-performance liquid chromatography (RP-HPLC). First, the capacity factors were determined for each drug at different concentrations of the organic modifier (methanol) at a constant flow rate, using an octadecylsilane column. The capacity factors were then extrapolated to zero methanol concentration to determine lipophilicity parameter, log kw. The resultant log kw values were correlated to previously reported lipophilicity parameters and good relationships were observed. Correlations were also established between log kw values and various structural parameters using CODESSA software. Excellent correlations, free from chance correlations and high predictive power, were obtained.

Research paper thumbnail of Study of azathioprine encapsulation into liposomes

Journal of Microencapsulation, 1998

The factors influencing the encapsulation of azathioprine (AZA) into liposomes were investigated ... more The factors influencing the encapsulation of azathioprine (AZA) into liposomes were investigated to find out the conditions for its optimal entrapment. Similar studies for comparison were also carried out on 6-mercaptopurine (6-MP), of which AZA is a prodrug. AZA and also 6-MP show higher encapsulation efficiencies in MLVs as compared to LUVs. Variation in phospholipid composition does not seem to affect the loading capacity of either of the two drugs. The encapsulation efficiency of both the drugs improves upon addition of cholesterol in the bilayer, but the effect is seen only up to 30% cholesterol. Thereafter the effect becomes constant. AZA shows better incorporation in the positively charged liposomes as compared to those with neutral or negative charge. The entrapment of 6-MP is, however, found to be independent of the charge on the liposomes. Entrapment efficiency for both the drugs markedly depends on the pH of the hydration medium, yielding better entrapment efficiencies at high pH values. The rise in solute concentration initially causes increase in the entrapment of the two drugs which is followed by a decreasing phase.

Research paper thumbnail of Quantitative structure property relationships for the adsorption of pharmaceuticals onto activated carbon

Quantitative structure-property relationship (QSPR) studies based on artificial neural network (A... more Quantitative structure-property relationship (QSPR) studies based on artificial neural network (ANN) and wavelet neural network (WNN) techniques were carried out for the prediction of solvent polarity. Experimental S′ values for 69 solvents were assembled. This set included saturated and unsaturated hydrocarbons, solvents containing halogen, cyano, nitro, amide, sulfide, mercapto, sulfone, phosphate, ester, ether, etc. Semi-empirical quantum chemical calculations at AM1 level were used to find the optimum 3D geometry of the studied molecules and different quantum-chemical descriptors were calculated by the HyperChem software. A stepwise MLR method was used to select the best descriptors and the selected descriptors were used as input neurons in neural network models. The results obtained by the two methods were compared and it was shown that in WNN, the convergence speed was faster and the root mean square error of prediction set was also smaller than ANN. The average relative error in WNN was 7.9 and 6.8% for calibration and prediction set, respectively, and the results showed the ability of the WNN developed here to predict solvent polarity.

Research paper thumbnail of Disodium pamidronate formulation

Research paper thumbnail of Solid oral pharmaceutical compositions of telmisartan, essentially free of surfactants

Research paper thumbnail of Pharmaceutical composition comprising a combination of eperisone and diclofenac and process for preparing thereof

Research paper thumbnail of Computer-Aided Instruction in Pharmaceutical Education: Retrospect and Prospects

Research paper thumbnail of In Silico ADME Predictions using Quantitative Structure Pharmacokinetic Relationships. Part II: Descriptors

Research paper thumbnail of Stability-indicating analysis of isoxazolyl penicillins using dual wavelength high-performance liquid chromatography

Journal of chromatography. B, Biomedical sciences and applications, Jan 24, 1998

Stability-indicating high-performance liquid chromatography analytical procedures were developed ... more Stability-indicating high-performance liquid chromatography analytical procedures were developed for specific determination of four isoxazolyl penicillins during degradation under neutral and accelerated acid/alkali conditions. The chromatographic conditions were set so that the drug peak was well separated from the peaks of the degradation products. Peak homogeneity of the resolving drug peak was assessed by the shape of the ratio chromatogram. Good and reproducible separations were achieved on a reversed-phase column using a mobile phase consisting of acetonitrile and a solution of 20 mM potassium dihydrogen phosphate plus 10 mM tetramethylammonium chloride in water (adjusted to pH 5). Optimal separations for all four drugs were achieved within the range of 15-21% organic modifier in the mobile phase. The detection wavelengths were 220 nm and 240 nm. The stability-indicating nature of the methods was confirmed by the linearity of the pseudo-first order plots. The utility of dual-w...

Research paper thumbnail of Correlation of Penicillin Structure with Rate Constants for Basic Hydrolysis

Pharmacy and Pharmacology Communications, 2000

The rates of degradation of 16 different penicillins have been determined at 35 C in borate buffe... more The rates of degradation of 16 different penicillins have been determined at 35 C in borate buffer, pH 9Á2, by use of stability-indicating HPLC assay procedures. The best-®t was sought between pseudo ®rst-order hydrolytic rate constants and different types of structural descriptor. Constitutional, topological, geometric and electrostatic descriptors were calculated using WHIM-3D=QSAR and CODESSA software. Advanced semi-empirical and ab-initio calculations were performed using AMPAC software. CODESSA was used to develop (multi)linear correlation models, perform cluster analysis of the experimental data and molecular descriptors, and interpret the developed models. The best correlations with the rates of hydrolysis of the drugs were found for topological, electrostatic and quantumchemical descriptors.

Research paper thumbnail of Quantitative structure–property relationships in pharmaceutical research – Part 1

Pharmaceutical Science & Technology Today, 2000

Quantitative structure-property relationship (QSPR) studies based on artificial neural network (A... more Quantitative structure-property relationship (QSPR) studies based on artificial neural network (ANN) and wavelet neural network (WNN) techniques were carried out for the prediction of solvent polarity. Experimental S′ values for 69 solvents were assembled. This set included saturated and unsaturated hydrocarbons, solvents containing halogen, cyano, nitro, amide, sulfide, mercapto, sulfone, phosphate, ester, ether, etc. Semi-empirical quantum chemical calculations at AM1 level were used to find the optimum 3D geometry of the studied molecules and different quantum-chemical descriptors were calculated by the HyperChem software. A stepwise MLR method was used to select the best descriptors and the selected descriptors were used as input neurons in neural network models. The results obtained by the two methods were compared and it was shown that in WNN, the convergence speed was faster and the root mean square error of prediction set was also smaller than ANN. The average relative error in WNN was 7.9 and 6.8% for calibration and prediction set, respectively, and the results showed the ability of the WNN developed here to predict solvent polarity.

Research paper thumbnail of Quantitative structure–property relationships in pharmaceutical research – Part 2

Pharmaceutical Science & Technology Today, 2000

Quantitative structure-property relationship (QSPR) studies based on artificial neural network (A... more Quantitative structure-property relationship (QSPR) studies based on artificial neural network (ANN) and wavelet neural network (WNN) techniques were carried out for the prediction of solvent polarity. Experimental S′ values for 69 solvents were assembled. This set included saturated and unsaturated hydrocarbons, solvents containing halogen, cyano, nitro, amide, sulfide, mercapto, sulfone, phosphate, ester, ether, etc. Semi-empirical quantum chemical calculations at AM1 level were used to find the optimum 3D geometry of the studied molecules and different quantum-chemical descriptors were calculated by the HyperChem software. A stepwise MLR method was used to select the best descriptors and the selected descriptors were used as input neurons in neural network models. The results obtained by the two methods were compared and it was shown that in WNN, the convergence speed was faster and the root mean square error of prediction set was also smaller than ANN. The average relative error in WNN was 7.9 and 6.8% for calibration and prediction set, respectively, and the results showed the ability of the WNN developed here to predict solvent polarity.

Research paper thumbnail of Lipophilic drug derivatives in liposomes

International Journal of Pharmaceutics, 1998

The drug molecules can be classified into four categories, ie highly hydrophilic, highly lipophil... more The drug molecules can be classified into four categories, ie highly hydrophilic, highly lipophilic, amphiphilic and those with biphasic insolubility. These are located differently in the liposomes and exhibit different entrapment and release behaviour. Problems like poor ...

Research paper thumbnail of RP-HPLC Determination of Lipophilicity of 22 Penicillins, Their Correlation with Reported Values and Establishment of Quantitative Structure-log Kw Relationships

QSAR & Combinatorial Science, 2005

ABSTRACT Lipophilicity parameters were determined for a series of 22 penicillins by the reversed ... more ABSTRACT Lipophilicity parameters were determined for a series of 22 penicillins by the reversed phase high-performance liquid chromatography (RP-HPLC). First, the capacity factors were determined for each drug at different concentrations of the organic modifier (methanol) at a constant flow rate, using an octadecylsilane column. The capacity factors were then extrapolated to zero methanol concentration to determine lipophilicity parameter, log kw. The resultant log kw values were correlated to previously reported lipophilicity parameters and good relationships were observed. Correlations were also established between log kw values and various structural parameters using CODESSA software. Excellent correlations, free from chance correlations and high predictive power, were obtained.

Research paper thumbnail of Study of azathioprine encapsulation into liposomes

Journal of Microencapsulation, 1998

The factors influencing the encapsulation of azathioprine (AZA) into liposomes were investigated ... more The factors influencing the encapsulation of azathioprine (AZA) into liposomes were investigated to find out the conditions for its optimal entrapment. Similar studies for comparison were also carried out on 6-mercaptopurine (6-MP), of which AZA is a prodrug. AZA and also 6-MP show higher encapsulation efficiencies in MLVs as compared to LUVs. Variation in phospholipid composition does not seem to affect the loading capacity of either of the two drugs. The encapsulation efficiency of both the drugs improves upon addition of cholesterol in the bilayer, but the effect is seen only up to 30% cholesterol. Thereafter the effect becomes constant. AZA shows better incorporation in the positively charged liposomes as compared to those with neutral or negative charge. The entrapment of 6-MP is, however, found to be independent of the charge on the liposomes. Entrapment efficiency for both the drugs markedly depends on the pH of the hydration medium, yielding better entrapment efficiencies at high pH values. The rise in solute concentration initially causes increase in the entrapment of the two drugs which is followed by a decreasing phase.

Research paper thumbnail of Quantitative structure property relationships for the adsorption of pharmaceuticals onto activated carbon

Quantitative structure-property relationship (QSPR) studies based on artificial neural network (A... more Quantitative structure-property relationship (QSPR) studies based on artificial neural network (ANN) and wavelet neural network (WNN) techniques were carried out for the prediction of solvent polarity. Experimental S′ values for 69 solvents were assembled. This set included saturated and unsaturated hydrocarbons, solvents containing halogen, cyano, nitro, amide, sulfide, mercapto, sulfone, phosphate, ester, ether, etc. Semi-empirical quantum chemical calculations at AM1 level were used to find the optimum 3D geometry of the studied molecules and different quantum-chemical descriptors were calculated by the HyperChem software. A stepwise MLR method was used to select the best descriptors and the selected descriptors were used as input neurons in neural network models. The results obtained by the two methods were compared and it was shown that in WNN, the convergence speed was faster and the root mean square error of prediction set was also smaller than ANN. The average relative error in WNN was 7.9 and 6.8% for calibration and prediction set, respectively, and the results showed the ability of the WNN developed here to predict solvent polarity.