Fraunhofer Institute for Molecular Biology and Applied Ecology IMEConsolidated octanol/water partition coefficients
Inherent variability in measued and calculated log Kow data
The octanol/water partition coefficient, commonly denoted as log KOW, quantifies the hydrophobicity of a chemical compound. It represents the ratio of the concentration of a chemical in octanol to its concentration in water at equilibrium. This coefficient is a critical parameter for predicting how substances behave in the environment, particularly in terms of their transport, bioaccumulation, and toxicity. The log KOW can be determined through several experimental methods (e.g. shake flask method; generator column method; slow stirring method, and chromatographic methods) as well as computational methods including quantitative structure-activity relationship (QSAR) models; fragment (group contribution) methods, linear solvation energy relationships (LSER), and machine learning techniques. The study conducted by Monika Nendza (AL-Luhnstedt) in collaboration with Verena Kosfeld and Christian Schlechtriem (Fraunhofer IME) examines the variability and uncertainty associated with octanol/water partition coefficients (log KOW). Analyzing 231 diverse case study chemicals as part of a UBA funded project, the authors found that log KOW values can vary significantly by over 1 log unit, depending on the method used for their determination, but independent of experimental or computational methods. To address the inconsistencies, the researchers advocate for a consensus modeling approach that aggregates multiple log KOW estimates through a weight-of-evidence (WoE) or averaging methodology. This approach aims to provide robust and reliable log KOW values by consolidating data from various sources, thereby reducing the risk of bias from individual erroneous estimates. The resulting consolidated log KOW values demonstrate reduced variability, typically within 0.2 log units, offering a more scientifically valid basis for hazard and risk assessments of chemicals. Overall, the study emphasizes the need for harmonized methods in deriving log KOW values to enhance their reliability in environmental risk assessments.