Pharmacokinetic/Pharmacodynamic Translation and Model-Informed Drug Development for Oligonucleotide Therapeutics

Abstract

Small interfering RNAs (siRNAs) and antisense oligonucleotides (ASOs) have emerged as clinically validated therapeutic modalities, with approvals and late-stage development programs spanning rare genetic, neurologic, cardiovascular, metabolic, and infectious diseases. Despite these advances, oligonucleotide development presents unique challenges compared with small molecules and biologics, including rapid plasma distributive clearance, nuclease-mediated degradation, limited extrahepatic distribution, and prolonged pharmacodynamic effects driven by tissue retention and intracellular mechanisms such as RNA-induced silencing complex loading or RNase H-mediated activity. Consequently, tissue disposition and intracellular pharmacology most often govern therapeutic response more directly than plasma exposures alone, complicating conventional approaches to dose selection, efficacy prediction, and safety assessment. Model-informed drug development (MIDD) offers a quantitative framework to address these challenges through integration of preclinical, translational, and clinical data into empirical, mechanistic, and systems-level models. This review summarizes current and emerging MIDD applications in oligonucleotide therapeutics, with primary emphasis on siRNAs and complementary insights from ASOs. Approaches discussed include empirical and semi-mechanistic pharmacokinetic/pharmacodynamic (PK/PD) models, physiologically based pharmacokinetic (PBPK) frameworks describing tissue-selective biodistribution and intracellular disposition, and quantitative systems pharmacology (QSP) models linking molecular target modulation with downstream biologic and clinical responses. Collectively, these approaches have supported cross-species translation; human dose selection; clinical trial optimization; and mechanistic understanding of oligonucleotide absorption, distribution, metabolism, excretion, and pharmacology. Finally, we discuss future opportunities and remaining challenges for MIDD in oligonucleotide therapeutics, including enabling extrahepatic delivery, characterizing interindividual variability, and integrating systems-level and data-driven approaches to improve translational predictability and accelerate development of next-generation oligonucleotide medicines.