Revisiting the in-vitro and in-vivo considerations for in-silico modelling of complex injectable drug products.

Complex injectable drug products (CIDPs) have often been developed to modulate the pharmacokinetics along with efficacy for therapeutic agents used for remediation of chronic disorders. The effective development of CIDPs has exhibited complex kinetics associated with multiphasic drug release from the prepared formulations. Consequently, predictability of pharmacokinetic modelling for such CIDPs has been difficult and there is need for advanced complex computational models for the establishment of accurate prediction models for in-vitro-in-vivo correlation (IVIVC). The computational modelling aims at supplementing the existing knowledge with mathematical equations to develop formulation strategies for generation of predictable and discriminatory IVIVC. Such an approach would help in reduction of the burden of effect of hidden factors on preclinical to clinical translations. Computational tools like physiologically based pharmacokinetics (PBPK) modelling have combined physicochemical and physiological properties along with IVIVC characteristics of clinically used formulations. Such techniques have helped in prediction and understanding of variability in pharmacodynamic parameters of potential generic products to clinically used formulations like Doxil®, Ambisome®, Abraxane® in healthy and diseased population using mathematical equations. The current review highlights the important formulation characteristics, in-vitro , preclinical in-vivo aspects which need to be considered while developing a stimulatory predictive PBPK model in establishment of an IVIVC and in-vitro-in-vivo relationship (IVIVR). [Display omitted] • Generic CIDP drug product development has been challenging due to unabridged complex BE studies. • CIDP's exhibit flip-flop pharmacokinetics characterised by multiphasic drug release profiles. • IVIVC presents improved product development having higher predictability for bioequivalence. • Predictive modelling development is based on all factors affecting the in-vivo CIDPs performance. • Governed by different mechanism of dissolution, each CIDP's require customized in silico models. [ABSTRACT FROM AUTHOR]