Dependence of the kinetic and thermodynamic parameters on hydrophilic-lipophilic character of alprazolam, clonazepam, diazepam, doxepin and haloperidol in alkaline environment

Examination of the stability of clonazepam, diazepam, alprazolam, haloperidol, and doxepin in basic solutions was performed, together with an assessment of the kinetic (k, t0.1i t0.5) and thermodynamic (Ea, ΔH(++)i ΔS(++)) stability-indicating parameters, which were compared with the lipophilicity (logP) of the studied drugs. It was observed that the calculated values of Ea, ΔH(++) and ΔS(++) for the studied drugs increased from 41.04 kJ/mol to 125.50 kJ/mol, from 37.82 kJ/mol to 122.24 kJ/mol and from -167.09 J/Kmol to 53.02 J/Kmol, respectively, along with an increase of lipophilicity (logP) from 2.12 to 4.30 for the most hydrophilic alprazolam to the most lipophilic haloperidol. The degradation products were identified using UPLC/MS/MS method.

Current mathematical methods used in QSAR/QSPR studies

This paper gives an overview of the mathematical methods currently used in quantitative structure-activity/property relationship (QASR/QSPR) studies. Recently, the mathematical methods applied to the regression of QASR/QSPR models are developing very fast, and new methods, such as Gene Expression Programming (GEP), Project Pursuit Regression (PPR) and Local Lazy Regression (LLR) have appeared on the QASR/QSPR stage. At the same time, the earlier methods, including Multiple Linear Regression (MLR), Partial Least Squares (PLS), Neural Networks (NN), Support Vector Machine (SVM) and so on, are being upgraded to improve their performance in QASR/QSPR studies. These new and upgraded methods and algorithms are described in detail, and their advantages and disadvantages are evaluated and discussed, to show their application potential in QASR/QSPR studies in the future.