The active pharmaceutical ingredient (API) in long acting injectable (LAI) products is usually delivered into the system circulation in form of microspheres. Currently, bioequivalence guidance of generic formulations requires both qualitatively (Q1) and quantitatively (Q2) the same as the reference-listed drug. Usually parallel bioequivalence (BE) study is recommended. This is very challenging due to high inter-subject variability, complex pharmacokinetic and pharmacodynamic (PKPD) profiles, study length and expenditure. This research proposes data-fusion based platform for population PKPD modeling and statistical analysis to assist development of generic LAI products. The integrated platform of mechanistic and data-driven models is developed for bioequivalence testing and covariate assessment of generic LAI products. The new platform will be validated with the target product and its generic forms. The deterministic models are the existing population PKPD models and they are supplemented with statistical process models to minimize uncertainties into account. Subject Evolution Modeling (SEM), Subject Level Modeling (SLM), and prediction modeling will allow all challenges of clinical evaluations to be addressed with minimum uncertainty and high level of robustness. The integrated models are imbedded in Monte Carlo simulation to determine feasible ranges of covariate variability, which are used for optimizing drug dosage while meeting safety and efficacy requirement.
The integrated platform of mechanistic and data-driven models is developed for bioequivalence testing and covariate assessment of generic LAI products. The new platform will be validated with the target product and its generic forms, and Subject Evolution Modeling (SEM), Subject Level Modeling (SLM), and prediction modeling will allow all challenges of clinical evaluations to be addressed with minimum uncertainty and high level of robustness. The integrated models are imbedded in Monte Carlo simulation to determine feasible ranges of covariate variability and covariate variation are used for optimizing drug dosage.
