In vivo–In Vitro correlation (IVIVC) in drug development: bridging preclinical and clinical outcomes for regulatory approvals

Abstract

The pharmacological discipline of In vivo–In Vitro Correlation (IVIVC) plays a crucial role in drug development, creating essential relationships to forecast in vivo PK results from measuring In Vitro drug release profiles. IVIVC models not only prove essential for formulating drugs properly but also significantly reduce time and costs during regulatory processes, thereby limiting extensive clinical testing requirements. These models can predict live performance outcomes through laboratory results, leading to consistent therapeutic outcomes between different medications. The relation between In Vitro and in vivo data determines IVIVC level classification which includes Levels A, B, C and multiple Level C. Level A IVIVC represents the most accurate predictive tool because it establishes direct mathematical links between dissolution data and PK parameters. The U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) not only permit IVIVC as an important development tool for formulation approval but also provide validation and practical implementation standards, instilling confidence in its regulatory acceptance. The development process for IVIVCs faces multiple difficulties which include variations in biological statuses and intricate drug-release systems as well as reduced predictive precision for select drug formulations. However, the advancement of computational modeling and biorelevant dissolution testing with machine learning techniques is leading to the enhancement of IVIVC methodology development. Excitingly, future investigations are attempting to make IVIVC more effective for usage in difficult drug formulations such as extended-release medications and drugs that belong to BCS Groups II and IV, promising potential advancements in IVIVC.