How Well Do Lipophilicity Parameters, MEEKC Microemulsion Capacity Factor, and Plasma Protein Binding Predict CNS Tissue Binding?

Brain fraction unbound (Fu) is critical to understanding the pharmacokinetics/dynamics of central nervous system (CNS) drugs, thus several surrogate predictors have been proposed. At present, correlations between brain Fu, microemulsion electrokinetic chromatography capacity factor (MEEKC k′), plasma Fu, octanol-water partition coefficient (clogP), and LogP at pH 7.4 (clogD7.4) were compared for 94 diverse molecules, and additionally for 587 compounds. MEEKC k′ was a better predictor of brain Fu (r2 = 0.74) than calculated lipophilicity parameters (clogP r2 = 0.51–0.54, clogD7.4r2 = 0.41–0.44), but it was not superior to plasma Fu (r2 = 0.74–0.85) as a predictor of brain Fu. MEEKC k′ did not predict plasma Fu(r2 = 0.58) as well as brain Fu, and the extent of improvement over clogP or clogD7.4 (r2 = 0.41–0.49) was less pronounced. Although log–log-correlation analysis supported seemingly strong prediction of brain Fu both by MEEKC k′ and by plasma Fu (r2 ≥ 0.74), analysis of prediction error estimated a 10-fold and 6.9–8.6-fold prediction interval for brain Fu estimated using MEEKC k′ and plasma Fu, respectively. Therefore, MEEKC k′ and plasma Fu can predict the log order of CNS tissue binding, but they cannot provide truly quantitative brain Fu predictions necessary to support in-vitro-to-in-vivo extrapolations and pharmacokinetic/dynamic data interpretation. © 2012 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:1932–1940, 2012