A multiscale physiologically based pharmacokinetic model to support mRNA-encoded BiTE therapy in cancer treatment

In the field of cancer therapy, bispecific T cell engagers (BiTEs) have demonstrated significant potential. However, their clinical application is constrained by challenges in production and limited plasma half-life. In vitro-transcribed (IVT) mRNA formulations emerge as a promising alternative, offering adaptability and cost-efficiency. Yet, the intricate relationship between mRNA dosage, antibody production, and the distribution of mRNA and proteins requires a deeper understanding. To address these issues, we present a novel physiologically based pharmacokinetic (PBPK) model to characterize the pharmacokinetics of BiTEs. This model predicts the distribution patterns of both recombinant and mRNA-encoded BiTEs by extending an established PBPK model with a hierarchical multiscale framework calibrated and validated using preclinical data from existing literature. The extended PBPK model can be adapted to various mRNA-based therapeutic formulations, facilitating in-silico exploration of d...

In the field of cancer therapy, bispecific T cell engagers (BiTEs) have demonstrated significant potential. However, their clinical application is constrained by challenges in production and limited plasma half-life. In vitro-transcribed (IVT) mRNA formulations emerge as a promising alternative, offering adaptability and cost-efficiency. Yet, the intricate relationship between mRNA dosage, antibody production, and the distribution of mRNA and proteins requires a deeper understanding. To address these issues, we present a novel physiologically based pharmacokinetic (PBPK) model to characterize the pharmacokinetics of BiTEs. This model predicts the distribution patterns of both recombinant and mRNA-encoded BiTEs by extending an established PBPK model with a hierarchical multiscale framework calibrated and validated using preclinical data from existing literature. The extended PBPK model can be adapted to various mRNA-based therapeutic formulations, facilitating in-silico exploration of different drug administration scenarios. It can provide valuable support for optimizing dose and schedule and allows the efficient investigation of drug distribution at a whole-body scale. This approach promises to enhance the personalization and effectiveness of cancer therapies, reduce research time and costs, and significantly advance the development of mRNA-based BiTEs for cancer treatment.