Introducing a computational method to estimate and prioritize systemic body exposure of organic chemicals in humans using their physicochemical properties

Authors: Matthews EJ
Publication: Computational Toxicology
Software: ADMET Predictor®


This report describes a computational method developed to predict systemic exposure (s-exposure), chemical disposition {(CD) intestinal absorption, transport, membrane permeability, distribution, sequestration, phospholipidosis and toxicokinetics} of organic chemicals in humans. The method qualitatively and quantitatively estimates a chemical’s CD activity profile based upon computed molecular descriptor properties (descriptors), and it facilitates in silico signal-detection of data-gaps, prioritization, risk-ranking, read-across, and re-assessments (if mandated) of large sets of chemicals in a safety evaluation setting. The investigation used a reference set of 2372 marketed human pharmaceuticals to define decision rules for an optimal chemical space (OCS) in which chemicals have high s-exposure, good CD, and a potential for chemical toxicity (CT); conversely, chemicals outside the OCS have low s-exposure, poor CD into the body, and low potential for CT. The method requires computation of 29 descriptors, identification of OCS molecular descriptor property violations (descriptor_violations), and alignment of descriptor_violations with specific decision rules for individual CD endpoint activities. The investigation predicted the CD activities of food and cosmetic preservatives, ingredients in GRAS (generally recognized as safe). Notices submitted to the FDA, reference pharmaceuticals, and it provides prioritization metrics and indices that facilitate prioritization of chemical in silico computed CD activities.