Model-Informed Drug Development Applications and Opportunities in mRNA-LNP Therapeutics

Abstract

The utilization of lipid nanoparticles (LNP) for encapsulating mRNA has revolutionized the field of therapeutics, enabling the rapid development of COVID-19 vaccines and cancer vaccines. However, the clinical development of mRNA-LNP therapeutics faces numerous challenges due to their complex mechanisms of action and limited clinical experience. To overcome these hurdles, Model-Informed Drug Development (MIDD) emerges as a valuable tool that can be applied to mRNA-LNP therapeutics, facilitating the evaluation of their safety and efficacy through the integration of data from all stages into appropriate modeling and simulation techniques. In this review, we provide an overview of current MIDD applications in mRNA-LNP therapeutics clinical development using in vivo data. A variety of modeling methods are reviewed, including quantitative system pharmacology (QSP), physiologically based pharmacokinetics (PBPK), mechanistic pharmacokinetics/pharmacodynamics (PK/PD), population PK/PD, and model-based meta-analysis (MBMA). Additionally, we compare the differences between mRNA-based therapeutics, small interfering RNA, and adeno-associated virus-based gene therapies in terms of their clinical pharmacology, and discuss the potential for mutual sharing of MIDD knowledge between these therapeutics. Furthermore, we highlight the promising future opportunities for applying MIDD approaches in the development of mRNA-LNP drugs. By emphasizing the importance of applying MIDD knowledge throughout mRNA-LNP therapeutics development, this review aims to encourage stakeholders to recognize the value of MIDD and its potential to enhance the safety and efficacy evaluation of mRNA-LNP therapeutics.