Chemometrics aids in analysis of interactions between antiretroviral drugs and food

Use of a chemometric approach appears helpful in the evaluation of interactions between antiretroviral medications and food, suggests a recent study.

A total of 33 antiretroviral drugs were included in the analysis: 10 nucleoside reverse transcriptase inhibitors (NRTIs), six non-NRTIs, five integrase strand transfer inhibitors, 10 protease inhibitors, one fusion inhibitor, and one HIV maturation inhibitor. The investigators obtained the input data from published clinical studies, chemical records, and calculations.

In addition, a hierarchical partial least squares (PLS) model was constructed with three response parameters, namely postprandial change of time to reach maximum drug concentration (ΔT_max), albumin binding (%), and logarithm of partition coefficient (logP). Principal component analysis (PCA) models for six groups of molecular descriptors had predictor parameters as the first principal components.

PCA models explained 64.4 percent to 83.4 percent of the variance of the original parameters (average 76.9 percent). On the other hand, the PLS model involved four significant components and explained 86.2 percent and 71.4 percent of the variance in the sets of predictor and response parameters, respectively.

Overall, 58 significant associations were observed between ΔT_max, albumin binding (%), logP and constitutional, topological, hydrogen bonding and charge-based molecular descriptors.

“Different physiochemical properties deriving from the chemical structures of antiretroviral drugs may contribute to the variable food effect,” the investigators said. “Chemometric methods allow analysing a large number of interrelated variables concomitantly and visualizing correlations between them.”