The Pharmaceutical Sciences Department is offering this grant to develop PBPK model-based mechanistic IVIVCs for Long Acting Injectable Suspensions and Implants.

The objective of this research proposal is to develop physiologically based pharmacokinetic (PBPK) model-based mechanistic in vitro in vivo correlations (IVIVCs) for two major types of long acting injectables (LAIs) such as crystalline suspensions and polymer-based implants by considering their distinct characteristics. The goal of the project is to develop a bottom-up mechanistic PBPK model for these two LAI categories by accounting for the influence of critical formulation attributes of each LAI drug product type to predict its in vivo release mechanism. The model formulation parameters and relevant physiology should be informed with suitable in vitro and in vivo experiments. A suitable preclinical animal model can be used to validate the PBPK model based IVIVCs for both LAI suspensions and polymer based implants.

The use of PBPK modelling provides a unique opportunity to understand how the physicochemical properties of drug molecules/polymer, implant specific properties, critical formulation attributes, and physiology, among other things, influence the in vivo release mechanisms of LAI drug products and their disposition characteristics. Moreover, once developed, a mechanistic PBPK model can help to define the ‘safe space’ for critical formulation attributes relevant to the reference listed drug (RLD) product, explain sources of PK variability and extrapolate predictions to human subjects by leveraging animal model data and by accounting for species-specific physiological differences. 

The objective of this research proposal is to develop physiologically based pharmacokinetic (PBPK) model-based mechanistic in vitro in vivo correlations (IVIVCs) for two major types of long acting injectables (LAIs) such as crystalline suspensions and polymer-based implants by considering their distinct characteristics. The goal of the project is to develop a bottom-up mechanistic PBPK model for these two LAI categories by accounting for the influence of critical formulation attributes of each LAI drug product type to predict its in vivo release mechanism. The model formulation parameters and relevant physiology should be informed with suitable in vitro and in vivo experiments. A suitable preclinical animal model can be used to validate the PBPK model based IVIVCs for both LAI suspensions and polymer based implants.

The use of PBPK modelling provides a unique opportunity to understand how the physicochemical properties of drug molecules/polymer, implant specific properties, critical formulation attributes, and physiology, among other things, influence the in vivo release mechanisms of LAI drug products and their disposition characteristics. Moreover, once developed, a mechanistic PBPK model can help to define the ‘safe space’ for critical formulation attributes relevant to the reference listed drug (RLD) product, explain sources of PK variability and extrapolate predictions to human subjects by leveraging animal model data and by accounting for species-specific physiological differences. 

The objective of this research proposal is to develop physiologically based pharmacokinetic (PBPK) model-based mechanistic in vitro in vivo correlations (IVIVCs) for two major types of long acting injectables (LAIs) such as crystalline suspensions and polymer-based implants by considering their distinct characteristics. The goal of the project is to develop a bottom-up mechanistic PBPK model for these two LAI categories by accounting for the influence of critical formulation attributes of each LAI drug product type to predict its in vivo release mechanism. The model formulation parameters and relevant physiology should be informed with suitable in vitro and in vivo experiments. A suitable preclinical animal model can be used to validate the PBPK model based IVIVCs for both LAI suspensions and polymer based implants.

The use of PBPK modelling provides a unique opportunity to understand how the physicochemical properties of drug molecules/polymer, implant specific properties, critical formulation attributes, and physiology, among other things, influence the in vivo release mechanisms of LAI drug products and their disposition characteristics. Moreover, once developed, a mechanistic PBPK model can help to define the ‘safe space’ for critical formulation attributes relevant to the reference listed drug (RLD) product, explain sources of PK variability and extrapolate predictions to human subjects by leveraging animal model data and by accounting for species-specific physiological differences. 

The objective of this research proposal is to develop physiologically based pharmacokinetic (PBPK) model-based mechanistic in vitro in vivo correlations (IVIVCs) for two major types of long acting injectables (LAIs) such as crystalline suspensions and polymer-based implants by considering their distinct characteristics. The goal of the project is to develop a bottom-up mechanistic PBPK model for these two LAI categories by accounting for the influence of critical formulation attributes of each LAI drug product type to predict its in vivo release mechanism. The model formulation parameters and relevant physiology should be informed with suitable in vitro and in vivo experiments. A suitable preclinical animal model can be used to validate the PBPK model based IVIVCs for both LAI suspensions and polymer based implants.

The use of PBPK modelling provides a unique opportunity to understand how the physicochemical properties of drug molecules/polymer, implant specific properties, critical formulation attributes, and physiology, among other things, influence the in vivo release mechanisms of LAI drug products and their disposition characteristics. Moreover, once developed, a mechanistic PBPK model can help to define the ‘safe space’ for critical formulation attributes relevant to the reference listed drug (RLD) product, explain sources of PK variability and extrapolate predictions to human subjects by leveraging animal model data and by accounting for species-specific physiological differences.