Characterization of the hepatic distribution of oligonucleotide therapeutics using a cross-species biologics PBPK model
Abdallah Derbalah (1), Felix Stader (1), Cong Liu (1), Armin Sepp (1).
(1) Certara UK Ltd., Simcyp division, Level 2-Acero, 1 Concourse Way, Sheffield, S1 2BJ, UK.
Introduction: Oligonucleotide therapeutics represent a promising novel treatment modality that has gained wide traction in the past few years due to its unique mechanism of action and therapeutic potential in many disease areas. These agents can regulate the gene expression of any target protein regardless of its cellular location by degrading/modifying its encoding mRNA; thus, opening new opportunities to modify the disease process. Despite having similar therapeutic modes of action, oligonucleotide therapeutics can vary in size, structure, and chemical modifications depending on the specific application. For example, anti-sense oligonucleotides (ASO) are made of single-stranded DNA, while small interfering RNA (siRNA) represents double-stranded RNA. As a rule, the nucleotides in these molecules are often chemically modified to improve stability and the molecule itself may carry conjugates, such as a triantennary N-acetylgalactosamine (GN3) conjugation to target a specific organ (i.e. liver). Given that the mRNA target specificity lies in the sequence of the oligos composed of similar nucleotide units, the drug metabolism and pharmacokinetics (DMPK) properties of different molecules are relatively well conserved from one asset to another. Since the liver is the primary site of action, escpecially for GN3-conjugated oligonucleotides, characterising liver distribution of different types of oligonucleotides can be of paramount importance to predicting the therapeutic effect of new agents.
Objectives: To develop a mechanistic whole-body physiologically based pharmacokinetic (PBPK) model to predict oligonucleotide therapeutics PK with special focus on liver as the primary site of exposure and catabolism.
Methods: This study utilised a whole-body cross-species biologics PBPK model [1], that was developed in SimBiology® (MATLAB®, Natick, Massachusetts: The MathWorks Inc.). The model incorporates physiological and mechanistic knowledge that govern the pharmacokinetics of large molecules in four different species, namely, mice, rats, monkeys, and humans. The model was modified by incorporating an intracellular compartment within the liver as well as two processes for oligonucleotides uptake by the liver. The first process represented the non-saturable non-specific uptake through fluid-phase endocytosis and non-specific non-saturable scavenger receptors, which was modelled by a first-order uptake reaction. The second process was the asialoglycoprotein receptor (ASGPR)-mediated uptake of GN3-conjugated oligonucleotides which was modelled through a receptor-mediated uptake model similar to the target-mediated drug disposition (TMDD) models for therapeutic proteins. Published preclinical liver data of a nonconjugated ASO was used to estimate the first-order uptake process [2]. Then, the receptor mediated liver-uptake was characterised using published liver data for a GN3-conjugated ASO [2] and a GN3-conjugated siRNA [3]. The model was validated against published mice plasma and liver data of a different GN3-siRNA from [3].
Results: For the unconjugated ASO, the estimated first-order uptake rate constant was 0.433 hour-1. The model well described the time profiles of both total liver and hepatocyte drug concentrations. This indicates that the model's mechanistic prediction solely based on the molecular weight of the drug was able to accurately predict the drug profile in extracellular compartments of the liver, including vascular and interstitial compartments. After fixing the endocytosis mediated uptake for GN3-conjugated siRNA, parameters of the receptor mediated endocytosis were estimated. The fitted model was able to predict both the plasma and liver profiles of the validation data reasonably well.
Conclusions: A whole-body PBPK model for oligonucleotides has been developed. The model can predict the liver distribution of both unconjugated and GN3-conjugated oligonucleotides and can be useful in developing new therapeutic oligonucleotides.
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