QRAR Models for Central Nervous System Drugs using Biopartitioning Micellar Chromatography

Abstract

The capability of biopartitioning Micellar Chromatography, BMC, to describe and estimate pharmacokinetic and pharmacodynamic parameters of central nervous system drugs is reviewed in this article. BMC is a mode of micellar liquid chromatography, MLC, that uses micellar mobile phases of Brij35 (polyoxyethilene(23) lauryl ether) prepared in physiological conditions (pH, ionic strength). The retention of a drug in this system depends on its hydrophobic, electronic and steric properties, which also determine its biological activity. The results of BMC studies suggest that this in vitro approach is an attractive useful tool to be implemented into the lead optimization step of drug development scheme.

Quantitative retention–activity relationship models for quinolones using biopartitioning micellar chromatography

“…The second-order polynomial models agree with the type of dependence that has been proved to be usual in QSAR models (Gringauz, 1997;Quiñones-Torrelo et al, 2002). It has also been demonstrated in previous QRAR studies that this is the usual retention-activity relationship for pharmacokinetics and the biological response of drugs (Quiñones-Torrelo et al, 1999;EscuderGilabert et al, 2000).…”

“…To evaluate the predictive ability of the QRAR models, the comparison between the root mean squared error of calibration (RMSEC), the root mean squared error of cross-validation (leave-one-out) (RMSECV) and the root mean squared error of cross-validation (leave-one-out) for interpolated data (RMSECVi) (Quiñones-Torrelo et al, 2002) was used. Table 1 shows the equations and the characteristics.…”

“…In order to obtain predictive and interpretative models, the relationships between the retention values and the corresponding bioactivities (half-life, T 1/2 , clearance, CL, volume of distribution. V d , plasma protein combination rate, P%, area under concentration-time curve, AUC, and the toxicity, LD 50 ) were investigated using equations (2) and (3), respectively (Quiñones-Torrelo et al, 2002).…”

Mixed micellar liquid chromatography methods: modelling quantitative retention–activity relationships of angiotensin converting enzyme inhibitors

“…To estimate the predictive ability of the QRAR models, three important parameters were proposed, which were the root mean squared error of calibration (RMSEC), root mean squared error of cross-validation (leave-one-out) (RMSECV) and root mean squared error of cross-validation (leave-one-out) for interpolated data (RMSECVi) (Quiñones-Torrelo et al, 2002).…”

“…In order to improve the model's reliability, some statistics could be added to the regression analysis. To insure the significance of the coefficients, it seems to be reasonable to use their confidence limits (Quiñones-Torrelo et al, 2002). From the results, we could see for the BMC Brij35 -QRAR models that all the fitting parameters of models were significant at the 95% confidence level (p-values were less than 0.05), while for the T 1/2 QRAR model at pH 6.5 the fitting parameters b and c, and at pH 7.4 the fitting parameter c, for the V d QRAR model at pH 7.4 the fitting parameter α, and for the IC50 QRAR model at pH 7.4 the fitting parameter c were not.…”