The block relevance (Br) analysis makes the choice of methods for measuring lipophilicity and permeability safer and speeds up drug candidate prioritization

The Block Relevance (BR) analysis with its recent implementation in MATLAB is a computational tool that allows deconvoluting the balance of intermolecular interactions governing a given drug discovery-related phenomenon described by a QSPR/PLS model. Here we discuss a few applications to show how BR analysis can make faster and more efficient the assessment of the drug-likeness of drug candidates. First, we describe how identifying the best chromatographic system provides reliable log Poct surrogates and log P in apolar environments. Then we focus on permeability and show how BR analysis allows to check the universality of passive permeability among cell types and the identification of the PAMPA method that provides the same pic-ture in terms of balance of intermolecular interactions as cell-based systems.