PURPOSE: To build a fast, user-friendly computational model to predict the intravitreal half-lives of drug-like compounds. METHODS: We used multivariate analysis to build intravitreal half-life models using two data sets, one with experimental data derived from both pigmented and albino rabbits and another including only data from experiments with albino rabbits. RESULTS: The final models had a Q(2) value of 0.65 and 0.75 for the mixed and albino rabbit models, respectively. The models performed well in predicting the intravitreal half-life of an external test set. In addition, the models are physiologically interpretable, containing mainly hydrogen bonding and lipophilicity descriptors. CONCLUSION: The developed models enable reliable predictions of intravitreal half-lives for use in the early drug development stages, without the need for prior experimental data.
PURPOSE: To build a fast, user-friendly computational model to predict the intravitreal half-lives of drug-like compounds. METHODS: We used multivariate analysis to build intravitreal half-life models using two data sets, one with experimental data derived from both pigmented and albino rabbits and another including only data from experiments with albino rabbits. RESULTS: The final models had a Q(2) value of 0.65 and 0.75 for the mixed and albino rabbit models, respectively. The models performed well in predicting the intravitreal half-life of an external test set. In addition, the models are physiologically interpretable, containing mainly hydrogen bonding and lipophilicity descriptors. CONCLUSION: The developed models enable reliable predictions of intravitreal half-lives for use in the early drug development stages, without the need for prior experimental data.
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: Felipe M González-Fernández; Annalisa Bianchera; Paolo Gasco; Sara Nicoli; Silvia Pescina Journal: Pharmaceutics Date: 2021-03-26 Impact factor: 6.321