Molecular Diagnosis to Individualized Therapies in Rare Genetic Diseases: New Approach Methodologies, RNA Therapeutics, and the Case for a Human-First Filter

Rare genetic diseases are heterogeneous across mechanisms, trajectories, and treatment responses. To date, approved therapies remain available for only a small proportion of rare genetic diseases. Oligonucleotide-based RNA therapeutics, particularly antisense oligonucleotides (ASOs) and small interfering RNAs (siRNAs), offer a promising therapeutic avenue for rare genetic diseases with sequence-level precision. However, traditional preclinical paths may mis-predict human outcomes when disease biology diverges from animal models. New approach methodologies (NAMs), including patient-derived induced pluripotent stem cells (iPSCs), organoid models, and clinical-trials-in-a-dish (CTiD), aim to bring human biology earlier into the translational pipeline. NAMs enable variant-to-function studies, efficacy screening, and safety triage at clinically relevant speed and scale. While critics argue that NAMs are unvalidated and cannot replace preclinical animal models, proponents report that they are increasingly able to recapitulate human phenotypes and predict clinical liabilities, although their predictive validity remains context-dependent. Here, a front-loaded human filter refers to the use of human-derived systems early in development to support mechanistic interpretation, candidate prioritization, and early liability assessment before broader nonclinical evaluation. Recent studies pairing NAMs with ASOs support rapid, patient-specific preclinical screening in selected settings, while also showing the need for broader evidence on delivery, pharmacology, safety, and clinical relevance. This review places these developments within the translational realities of oligonucleotide-based therapeutics, including model fidelity, ASO chemistry and optimization, delivery challenges, pharmacology, regulatory pathways for individualized ASOs, and accessibility. We also propose a pragmatic validation framework to assess the scientific and translational credibility of NAMs across rare genetic diseases.