Optimizing Oligonucleotide Therapeutics: A Model-Informed Drug Development Perspective

Area of Science:

• Pharmacology and Therapeutics
• Genetics and Molecular Biology
• Drug Development

Background:

• Oligonucleotide therapies (ASOs, siRNAs, aptamers) offer novel treatment strategies by targeting gene expression.
• Development challenges include a disconnect between drug levels in the body and effect in tissues, and limited clinical data for rare diseases.
• Traditional methods struggle with dose optimization and efficacy prediction for these complex therapeutics.

Purpose of the Study:

• To review the application of Model-Informed Drug Development (MIDD) in overcoming challenges specific to oligonucleotide therapeutics.
• To highlight how MIDD facilitates dose optimization, efficacy prediction, and decision-making in oligonucleotide drug development.
• To demonstrate the role of quantitative modeling in advancing oligonucleotide therapies and their regulatory success.

Main Methods:

• Comprehensive literature review of MIDD applications in FDA-approved oligonucleotide therapies.
• Analysis of how quantitative models bridge pharmacokinetic (PK) and pharmacodynamic (PD) disconnects.
• Examination of MIDD's role in informing clinical trial design, endpoint selection, and dosing strategies.

Main Results:

• MIDD successfully addresses the PK-PD disconnect in oligonucleotide therapies.
• Quantitative models enable dose optimization and efficacy prediction despite limited clinical data.
• MIDD has informed accelerated approvals, general and subpopulation dosing, and efficient clinical development.

Conclusions:

• MIDD is crucial for overcoming unique oligonucleotide development challenges.
• Quantitative modeling enhances the clinical and regulatory success of oligonucleotide therapeutics.
• MIDD strategies are essential for advancing this promising therapeutic class.