Jennifer Lang1, Helle Linnebjerg2, Emily Chen2, Giacomo Ruotolo2, Laura F. Michael2
1Eli Lilly & Company, 2Eli Lilly & Company
Introduction: SiRNAs are a drug modality that have gained significant interest in drug development in recent years [1]. LY3875383 is a GalNAc-conjugated small interfering RNA (GalNAc-siRNA) whose role is to reduce apolipoprotein-CIII (ApoC3) levels by preventing the APOC3 gene translation. ApoC3 acts as a potent inhibitor of lipoprotein lipase activity. Therefore, reduction of ApoC3 levels can decrease triglyceride (TG) levels that are highly associated with cardiovascular risk [2]. For GalNAc-siRNAs, hepatocyte internalisation via endocytosis is mediated by specific binding of the GalNAc conjugate to the asialoglycoprotein receptor (ASGPR). Due to the rapid liver uptake, GalNAc-siRNAs typically exhibit a short and transient plasma exposure (plasma half-lives less than 10 hours). In the endosomes, most GalNAc-siRNAs undergo endosomal degradation, whereas a small fraction is released as free/deconjugated siRNA in the cytoplasm. The free siRNAs bind to the RISC complex which results in mRNA degradation and lowering of target protein (i.e., pharmacodynamic effect) [3]. The residence time in liver measured in preclinical species is significantly prolonged (half-lives from weeks to months) compared to the plasma and correlates with the durable pharmacodynamic effect on the target protein. In this study, a population PK/PD model integrating a physiological liver compartment was developed to describe LY3875383 PK and PD effect on ApoC3, and the downstream effect on TG. Methods: LY3875383 was investigated in a phase 1 single-ascending dose study in healthy participants. Forty-one participants received either a single subcutaneous dose of LY3875383 (five dose levels) or placebo (i.e., 6 LY3875383:2 Placebo). Serial plasma PK samples were collected up to 72 h, then PK samples were measured bi-weekly up to day 85. ApoC3 and TG concentrations were monitored up to day 365 for the evaluation of pharmacodynamic effect. Plasma PK was described using a compartmental PK modelling approach. Subsequently, the drug is distributed to the hepatocytes via a well-stirred liver compartment, a surrogate for RISC-bound concentrations. The liver compartment was developed by calculating the volume based on individual body surface area. The PD effect is driven by the liver concentrations via the inhibition of ApoC3 production rate in a turnover model. Finally, the turnover model for TG is connected to the reduction of ApoC3 levels. Modelling was performed using NONMEM v7.5.0 using FOCE-I. Results: A two-compartment PK model with first-order absorption and linear elimination best described the plasma PK. As exposure increased in less than a dose proportional manner, the effect of dose levels on the absorption rate was included. Additionally, body weight on the central volume was found as a significant covariate (using a fixed allometric scaling factor of 1). Random effects were accounted for in the model via inter-individual variabilities on Ka, CL, V2 and Q and a combined residual error. The predicted liver clearance was 150-fold lower than the plasma clearance. ApoC3 levels were reduced by LY3875383 with a dose-response relationship. ApoC3 reduction was sustained after a single dose with the higher dose levels (greater than 100 mg) beyond day 169. The maximum ApoC3 knockdown was achieved with the highest dose level (change from baseline greater than 60% at day 71). The model also enabled to characterize the reduction of TG due to the inhibition of ApoC3 production rate. The effect of ApoC3 reduction on TG was described by the reduction of TG synthesis rate with an Emax model. TG levels decreased with increasing doses and decreasing ApoC3 levels (TG % change from baseline greater than 50% at day 71). Conclusion: A population PK/PD model was successfully developed using phase 1 data from healthy participants. This model included a liver compartment based on the mechanistic understanding of GalNAc siRNA disposition and enabled to describe the temporal difference in plasma PK and extended PD effect. The downstream effect of ApoC3 on TG was also modelled via an indirect response model, demonstrating the target engagement. This analysis provides a framework for model informed drug development (MIDD) to support the selection of dose regimens and the design of future clinical trials.
[1] X. Jing, V. Arya, K.S. Reynolds, H. Rogers, Drug Metab Dispos 51 (2023) 193–198. [2] D. Gaudet, V.J. Alexander, B.F. Baker, D. Brisson, K. Tremblay, W. Singleton, R.S. Geary, S.G. Hughes, N.J. Viney, M.J. Graham, R.M. Crooke, J.L. Witztum, J.D. Brunzell, J.J.P. Kastelein, N Engl J Med 373 (2015) 438–447. [3] V.S. Ayyar, D. Song, S. Zheng, T. Carpenter, D.L. Heald, J Pharmacol Exp Ther 379 (2021) 134–146.
Reference: PAGE 33 (2025) Abstr 11522 [www.page-meeting.org/?abstract=11522]
Poster: Drug/Disease Modelling - Other Topics