PURPOSE: The aim of this study was to develop quantitative structure pharmacokinetic relationships (QSPKR) to correlate drug physicochemical properties (molecular weight, lipophilicity, and drug solubility), dose, salt form factor, and eye pigmentation factor to intravitreal half-life in the rabbit model. METHODS: Dataset derived from prior literature reports, which included molecules with complete structural diversity, was used to develop the QSPKR models. Entire dataset as well as subsets limited to albino rabbit data, pigmented rabbit data, acids, bases, zwitterions, neutral compounds, suspensions, and macromolecules were analyzed. Multiple linear regression analysis was carried out with noncollinear independent variables and the best-fit models were selected based on correlation coefficients and goodness of fit statistics. RESULTS: The analysis indicated that logarithm of MW (Log MW), lipophilicity (Log P or Log D) and dose number (dose/solubility at pH 7.4), are the most critical determinants of intravitreal half-life of the compounds analyzed. The best-fit models obtained from the entire dataset (Log t (1/2) = -0.178 + 0.267 Log MW - 0.093 Log D + 0.003 dose/solubility at pH 7.4 + 0.153 Pigmentation Factor and Log t (1/2) = -0.32 + 0.432 Log MW - 0.157 Log P + 0.003 dose/solubility at pH 7.4) predicted the various subsets well. Pigmented dataset and zwitterions were better predicted by Log P rather than Log D. CONCLUSIONS: The present study confirmed that intravitreal half-life could be better predicted by a group of variables (Log MW, Log P or Log D, dose number) rather than a single variable. In general, increasing Log MW and dose number, while reducing Log D or Log P would be beneficial for prolonging intravitreal half-life of drugs.
PURPOSE: The aim of this study was to develop quantitative structure pharmacokinetic relationships (QSPKR) to correlate drug physicochemical properties (molecular weight, lipophilicity, and drug solubility), dose, salt form factor, and eye pigmentation factor to intravitreal half-life in the rabbit model. METHODS: Dataset derived from prior literature reports, which included molecules with complete structural diversity, was used to develop the QSPKR models. Entire dataset as well as subsets limited to albino rabbit data, pigmented rabbit data, acids, bases, zwitterions, neutral compounds, suspensions, and macromolecules were analyzed. Multiple linear regression analysis was carried out with noncollinear independent variables and the best-fit models were selected based on correlation coefficients and goodness of fit statistics. RESULTS: The analysis indicated that logarithm of MW (Log MW), lipophilicity (Log P or Log D) and dose number (dose/solubility at pH 7.4), are the most critical determinants of intravitreal half-life of the compounds analyzed. The best-fit models obtained from the entire dataset (Log t (1/2) = -0.178 + 0.267 Log MW - 0.093 Log D + 0.003 dose/solubility at pH 7.4 + 0.153 Pigmentation Factor and Log t (1/2) = -0.32 + 0.432 Log MW - 0.157 Log P + 0.003 dose/solubility at pH 7.4) predicted the various subsets well. Pigmented dataset and zwitterions were better predicted by Log P rather than Log D. CONCLUSIONS: The present study confirmed that intravitreal half-life could be better predicted by a group of variables (Log MW, Log P or Log D, dose number) rather than a single variable. In general, increasing Log MW and dose number, while reducing Log D or Log P would be beneficial for prolonging intravitreal half-life of drugs.
Authors: W Liu; Q F Liu; R Perkins; G Drusano; A Louie; A Madu; U Mian; M Mayers; M H Miller Journal: Antimicrob Agents Chemother Date: 1998-06 Impact factor: 5.191
Authors: David S Wishart; Craig Knox; An Chi Guo; Savita Shrivastava; Murtaza Hassanali; Paul Stothard; Zhan Chang; Jennifer Woolsey Journal: Nucleic Acids Res Date: 2006-01-01 Impact factor: 16.971
Authors: Henry F Edelhauser; Cheryl L Rowe-Rendleman; Michael R Robinson; Daniel G Dawson; Gerald J Chader; Hans E Grossniklaus; Kay D Rittenhouse; Clive G Wilson; David A Weber; Baruch D Kuppermann; Karl G Csaky; Timothy W Olsen; Uday B Kompella; V Michael Holers; Gregory S Hageman; Brian C Gilger; Peter A Campochiaro; Scott M Whitcup; Wai T Wong Journal: Invest Ophthalmol Vis Sci Date: 2010-11 Impact factor: 4.799
Authors: Chandrasekar Durairaj; Stephen J Kim; Henry F Edelhauser; Jaymin C Shah; Uday B Kompella Journal: Invest Ophthalmol Vis Sci Date: 2009-06-10 Impact factor: 4.799