Molecular properties that influence the oral bioavailability of drug candidates.

By D. Veber, Stephen R. Johnson, Hung‐Yuan Cheng, B. Smith, K. Ward, K. Kopple. Journal of Medicinal Chemistry, 2002

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Integrated deep learned transcriptomic and structure-based predictor of clinical trials outcomes (2016, background): “Nevertheless, the initial drug-likeness approach as well as the improved versions developed later (Veber et al. 2002; Ghose, Viswanadhan, and Wendoloski 1999) are not able to distinguish unacceptable toxicity profiles from safe ones (Bickerton et al. 2012; Leeson and Springthorpe 2007).”
Trend Analysis of a Database of Intravenous Pharmacokinetic Parameters in Humans for 670 Drug Compounds (2008, background): “Furthermore, the number of rotatable bonds was below the limit reported by Veber et al. (2002) for permeable compounds.”
Improved protein–ligand docking using GOLD (2003, methodology): “14,15 Here, we use the simpler rules to predict bioavailability derived by Veber et al. 16 Hence, in our “drug-like list,” only complexes from the “clean list” were included where the ligand has 10 or fewer rotatable bonds and a polar surface area (cid:1) 140 Å 2 .”
Computational Methods in Drug Discovery (2014, background): “For example, two additional criteria have been suggested that include the number of rotatable bonds being less than or equal to ten and the polar surface area being less than 140 Å2 (Veber et al., 2002).”
A data-driven approach to predicting successes and failures of clinical trials (2016, methodology): “In contrast, Veber’s rule (Veber et al., 2002) appears to be a far too conservative measure, with 75.”