The DIPPR process uses a systems approach in evaluating data from all available sources to triangulate on the best values, resulting in higher accuracy than could be achieved using only individual points. This approach includes hundreds of applied constraints on property values stemming from inter-property relationships, expected trends of properties between related chemicals, and the impact of chemical similarities and differences. Once these constraints are simultaneously satisfied for all properties, experts review the compound and give final approval for the compound to be added to the database. Each compound in the database therefore has recommended values for all properties and comments as to which of all reported property values is most reliable. When experimental data are not available, values for properties are predicted using both established methods as well as in-house prediction methodologies, and these predicted properties are subject to the same rigorous systems-level evaluation process.