Mohan Aparna1, Balakrishnan Chakrapani Narmada1, Chadalavada Sai Manasa1, Abhijeet Singh1, Kumar Rukmini2, Vikram Prabhakar2
1Vantage Research Pvt Ltd, 2Vantage Research Inc
Background Small interfering RNA (siRNA) regulates gene expression by targeting and degrading specific messenger RNA (mRNA), thus preventing protein synthesis. siRNAs are in development for correcting genetic disorders and managing chronic diseases. Better mechanistic understanding of the siRNA mechanism through modeling & simulation can enable prediction of Pharmacodynamic (PD) durability from the clinical Pharmacokinetic (PK) data and inform First in Human (FIH) dose prediction and dosing strategy. Objective Current public siRNA semi-mechanistic models predict the PD outcome of short acting siRNAs but are unable to predict PK/PD of long-acting siRNAs. To address this gap, we incorporate liver-specific intracellular processes(1), emphasizing RNA-induced silencing complex (RISC)-bound siRNA degradation rate, driven by the rate constant (kDR, units: 1/hour), which are believed to significantly impact PD. Our goal is to develop a QSP model capturing the clinical PK/PD of approved siRNA molecules to support drug development decisions of both short and long acting siRNAs. Methods In this study, we reproduce the PK/PD of a short acting siRNA Fitusiran from a published semi-mechanistic model Ayyar et al (2) while keeping the essence of the physiological mechanisms of absorption, distribution to site of action, cellular kinetics especially degradation rate of RISC-siRNA complex leading to reduction in target mRNA and protein expression. We expand the model with respect to siRNA cellular kinetics, re-evaluation of parameters and recalibration to capture PK/PD dynamics of five siRNAs: Fitusiran, Inclisiran, Olpasiran, Vutrisiran, and Lepodisiran (we have fitted to additional siRNAs captured in a PK modeling study performed earlier by Sten et al (3)). We thus further develop a unified set of physiological parameters (volumes, flow rates) and certain drug-specific, and species-specific parameters for data fitting. This enables us to identify associations between siRNA chemical modifications and PK/PD-sensitive parameters. Results and Discussion We reproduced the semi-mechanistic model from (2) and expanded model simulations to include mouse, monkey, and human PK/PD (PD as measured by reduction in target protein expression) for the short-acting siRNA, Fitusiran. We then evaluated whether the same parameters could describe the PK/PD of other short and long-acting siRNAs. While early plasma PK was captured reasonably well, later PK time points and PD were poorly described, indicating that the Ayyar model could not predict prolonged PK and PD behavior of long-acting siRNA therapies. We have further enhanced the predictive power and robustness of the model with sufficient physiological elements that allowed it to capture 5 siRNA drugs’ clinical PK/PD with different targets & varying PD durability, using a unified parameter set with changes in key drug-specific parameter, RISC degradation rate constant (kDR). Based on different chemical modifications (sugar, phosphorothioate, fluoro and methyl) done to the siRNA of interest, we developed a chemical modification score. We found significant correlation between kDR and chemical modification score proving that the chemical modification has a direct impact of stability that can be translated into a modeling parameter. Conclusions The newly expanded model effectively captures the clinical PK/PD of both short-acting and long-acting siRNA molecules. We are developing a robust translational modeling approach to go from preclinical cynomolgus monkey data to human clinical doses, as well as alternate dosing strategies for novel siRNA therapies.
[1] Hu, B., Zhong, L., Weng, Y., Peng, L., Huang, Y., Zhao, Y., & Liang, X. (2020). Therapeutic siRNA: state of the art. Signal Transduction and Targeted Therapy, 5(1). https://doi.org/10.1038/s41392-020-0207-x [2] Ayyar, V. S., Song, D., Zheng, S., Carpenter, T., & Heald, D. L. (2021). Minimal physiologically based Pharmacokinetic-Pharmacodynamic (MPBPK-PD) model of N-Acetylgalactosamine–Conjugated small interfering RNA disposition and gene silencing in preclinical species and humans. Journal of Pharmacology and Experimental Therapeutics, 379(2), 134–146. https://doi.org/10.1124/jpet.121.000805 [3] Sten, S., Cardilin, T., Antonsson, M., & Gennemark, P. (2023). Plasma pharmacokinetics of N-Acetylgalactosamine-Conjugated Small-Interfering ribonucleic acids (GaLNAC-Conjugated siRNAs). Clinical Pharmacokinetics, 62(12), 1661–1672. https://doi.org/10.1007/s40262-023-01314-7
Reference: PAGE 33 (2025) Abstr 11635 [www.page-meeting.org/?abstract=11635]
Poster: Drug/Disease Modelling - Other Topics