07-25, 16:55–17:05 (US/Eastern), Elm A
IVIVC.jl is a state of the art package for predictive mathematical modelling which correlates in vitro property (rate of drug dissolution) and in vivo response (plasma drug concentration profile). An IVIVC is meant to serve as a surrogate for in vivo bioavailability. This relationship can guide product development and support biowaivers. IVIVC.jl pipelines input bio-data to an IVIVC model with validations and it involves mathematical modelling, optimization and data visualisation accelerated with Julia.
In this talk, I will introduce IVIVC.jl, a state of the art package for pharmaceutical modelling and simulation-based in Julia. In the core, IVIVC.jl uses Optim.jl as optimization library to model the in-vitro data and then correlates the model with deconvoluted in vivo data. This package establishes three levels (A, B and C) of in vitro-in vivo correlation (IVIVC). IVIVC is the relationship between parameter derived from a pharmacokinetic property produced by a dosage form and a physicochemical property of the same dosage form. The pharmacokinetic properties include maximum plasma concentration (Cmax) or area under the plasma concentration-time curve (AUC). When an IVIVC correlation is established, it is used for development and optimization of drug formulations.
Using IVIVC.jl, one can accelerate drug development and can introduce a drug in the market faster. IVIVC can be used to substitute human bioequivalence studies in the initial approval process, the scale-up process, and the post-approval changes. This project is under the University of Maryland, Baltimore and the authors are me, Jogarao Gobburu and Vijay Ivaturi.
Shubham Maddhashiya is a third-year undergraduate student majoring in Ocean Engineering and Naval Architecture at the Indian Institute of Technology, Kharagpur, India. Shubham is interested in scientific computing and artificial intelligence in robotics.