Advancing siRNA Therapeutics with Pharmacometrics: A Review of Modeling Approaches and Clinical Applications.

Abstract

Small interfering RNA (siRNA) therapeutics represent a paradigm shift in targeting previously undruggable diseases through specific gene silencing. Since the FDA's first approval of patisiran in 2018, the field has expanded rapidly, with eight approved drugs and numerous clinical candidates. However, the atypical pharmacokinetic-pharmacodynamic (PK-PD) profile of siRNAs, characterized by rapid plasma elimination, prolonged tissue retention, and temporal dissociation between exposure and effect, has created distinct obstacles for conventional dose-finding strategies. This review examines how model-informed drug development, particularly pharmacometric modeling, has emerged as an essential tool in the advancement of siRNA therapeutics. Population PK-PD models for all FDA-approved siRNA drugs are systematically described, demonstrating that mechanistic and semi-mechanistic approaches inform preclinical-to-clinical translation, optimize dosing regimens, and support regulatory decisions. Key modeling frameworks include: (1) mechanistic models incorporating asialoglycoprotein receptor (ASGPR)-mediated uptake, RNA-induced silencing complex (RISC) loading, and mRNA degradation kinetics; (2) minimal physiologically-based PK-PD models for interspecies scaling; and (3) exposure-response models addressing the disconnect between plasma PK and pharmacological activity. This review also discusses how quantitative pharmacology addresses developmental challenges, including first-in-human dose selection, optimal dosing intervals, organ impairment effects, and interindividual variability. This pharmacometric perspective provides a quantitative framework for rational development of safe and effective siRNA therapeutics across diverse patient populations.