Predicting plasma and liver exposure in humans with a pharmacokinetic model for a GalNAc3-conjugated antisense oligonucleotide using sparse monkey data
Bergenholm Linnéa (1), Jansson-Löfmark Rasmus (1), Lee Richard (2), Yu Rosie (2), Antonsson Madeleine (1)
(1) Drug Metabolism and Pharmacokinetics, Cardiovascular, Renal and Metabolism, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden. (2) IONIS Pharmaceuticals, Carlsbad, California, US
Objectives: Optimal design of first time in human studies mainly relies on preclinical data for predicting drug exposure and pharmacodynamic effects. We developed a triantennary N-acetyl galactosamine (GalNAc3)-conjugated antisense oligonucleotide (ASOs) targeting the mRNA encoding for a specific protein prevalent in hepatocytes for the treatment of non-alcoholic steatohepatitis (NASH). Previous data propose that effective doses and plasma clearance scale from mouse with a factor of 5-10 [1,2] and monkey pharmacokinetics scale 1:1 [1]. The objectives of this study were to i.) assess the feasibility to predict plasma and liver ASO concentrations using a generic model for the pharmacokinetics of a GalNAc3-conjugated ASO, and ii.) to combine with a model for the turnover and inhibition of target mRNA in the liver based on TG mouse data in order to predict human dose and liver exposure and mRNA knockdown in the clinic.
Methods: We assessed the performance of a pharmacokinetic (PK) model for the 2´-O-methoxyethyl (2´-MOE) GalNAc3-ASO ISIS 681257 [3] in predicting the plasma and liver exposure of our candidate compound, a Gen 2.5 cEt GalNAc-ASO, in a 12 weeks high dose tolerability study in non-human primates. The model was also expanded by incorporating mRNA knock-down using exposure-response data from a 2 weeks study with 5 dose levels in human transgenic mice, similar to previously described [4,5]. The final model was used to predict plasma and liver exposure and mRNA knock-down in humans and estimate the dose-response. In addition, the dose-response was predicted by an allometric scaling approach applying a factor 7, in line with previous data [1,2]. Main assumptions are that the PK translates 1:1 based on body weight between NHP and human, that the liver exposure to mRNA reduction in TG human translates to human and that the human TG mouse knockdown is at steady state.
Results: We show that the model predicts both plasma and liver exposure as well as the plasma accumulation profile expected with a half-life of 4 weeks in the NHP tolerability study. Saturation in liver uptake at high doses is accounted for in the NHP model. Furthermore, 80% mRNA knock-down was predicted at a dose of 5 mg/week both by this approach and by allometric scaling of mouse dose-response data applying a factor 7. The similarity in the dose prediction applying these two different methods builds confidence in the dose prediction.
Conclusions: This translational approach relies on the similarities in PK of ASOs within the same chemistry, and our results indicate that pharmacokinetic information and the mathematical model for 2´-MOE chemistry GalNac-ASOs applies to cEt chemistry GalNac-ASOs. The dose-exposure-response prediction may be used to design pre-clinical and clinical studies. Plasma target engagement biomarkers are required to link data between animal and human for early validation of the mRNA reduction in liver prior to liver biopsies.
References:
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