Despite extensive study of liposomal drug formulations, reliable in vitro methods to monitor liposomal drug release and predict in vivo performance are still lacking. Currently, competing methods employed to assess liposomal release often produce disparate, method-specific release profiles. Progress in the development of robust, predictive release methods has been hindered by lack of systematic, quantitative characterization of these complex drug delivery systems with respect to the myriad of factors that may contribute to drug release profiles, the wide range of dissolution media employed, and a lack of mechanistic models that can reliably account for these critical factors on drug release. The proposed study combines evaluation of judiciously selected methods to monitor in vitro drug release from liposomal dosage forms with comprehensive mechanism-based computational models that incorporate the intra-liposomal microenvironment, dissolution media, and drug speciation (e.g., ionization state, membrane binding, complex formation, self-association, etc.). Method robustness will be assessed by statistical analyses of key mechanistic parameters that govern drug release (e.g., rate constants) as established by the mathematical models developed by the project team. The proposed mechanism-based models will enable analysts to extract those underlying parameters driving drug release, thereby unifying seemingly conflicting method-specific results, while providing scientifically founded in vitro-in vivo correlations (IVIVC). Though focused on liposomal formulations containing doxorubicin, the underlying project concepts will be applicable to release testing and IVIVC for other complex parenteral dosage forms such as polymeric micelles, nanosuspensions, and other nanotechnology-based drug delivery systems.
Specific aims are as follows: 1) Construct mechanism-based mathematical models for liposomal doxorubicin release, simulate release profiles, and analyze the sensitivity of current in vitro release methods to alterations in key model parameters due to formulation differences;2) Prepare and characterize liposome formulations similar in composition to marketed doxorubicin HCl liposome injections but varying in key selected properties (e.g., ammonium sulfate concentration, pegylation, particle size, etc.);3) Conduct dissolution/release studies of liposome formulations from aim 2 using in vitro release methods identified in aim 1, varying dissolution conditions to probe method performance and to validate/refine the mechanistic models to predict condition-specific release profiles;4) Adapt the release methods and validated mechanism-based mathematical models developed in previous aims to establish in vitro-in vivo correlations and thereby predict in vivo release profiles from in vitro experimental data. The expected outcome of these studies is to transform current empirically based testing approaches to one founded on a mechanistic understanding of the delivery system and its release characteristics in any given environment.
The proposed study combines a rigorous evaluation of experimental methods for monitoring in vitro drug release from complex liposomal dosage forms with comprehensive mechanism-based computational models that incorporate the intra-liposomal microenvironment, dissolution media, and drug speciation (e.g., ionization state, membrane binding, complex formation, self-association, etc.). The expected outcome of these studies is to transform current empirically based testing approaches to one founded on a mechanistic understanding of the delivery system and its release characteristics in any given environment.
| Csuhai, Eva; Kangarlou, Sogol; Xiang, Tian-Xiang et al. (2015) Determination of key parameters for a mechanism-based model to predict Doxorubicin release from actively loaded liposomes. J Pharm Sci 104:1087-98 |
| Fugit, Kyle D; Xiang, Tian-Xiang; Choi, Du H et al. (2015) Mechanistic model and analysis of doxorubicin release from liposomal formulations. J Control Release 217:82-91 |
