ProQR Therapeutics (PRQR) Status update summary

Pipeline and Development Strategy

• Lead program AX-0810 for cholestatic diseases is progressing as planned, with target engagement data in healthy volunteers expected this quarter and biliary atresia selected as the initial phase II indication.

• AX-0811, a next-generation NTCP-targeting oligonucleotide, shows threefold higher editing efficiency in preclinical models and is advancing rapidly, with CTA submission expected mid-year and initial clinical data by year-end 2026.

• AX-0422 for Hurler syndrome (MPS I) is advancing as a wholly owned asset, with CTA filing expected early 2027 and initial clinical data in the first half of 2027; the program aims to address both liver and CNS manifestations.

• AX-2911 targets PNPLA3 for MASH, showing superior reduction in liver fat compared to knockdown approaches, with an investigator-initiated trial planned in China and first-in-human trial expected H1 2027.

• The pipeline is supported by AI-driven discovery, high-throughput screening, and strategic partnerships, including ongoing collaboration with Eli Lilly, Ginkgo Bioworks, and the Rett Syndrome Research Trust.

Clinical and Preclinical Data Highlights

• AX-0810 demonstrated favorable safety and pharmacokinetics in healthy volunteers, with biomarker-based target engagement readouts pending and no safety signals observed.

• AX-0811 achieved around 60% editing efficiency in humanized mouse models, a significant improvement over previous generations, and ~3x higher editing efficiency over AX-0810.

• AX-0422 restored up to 20% of wild-type IDUA enzyme activity in preclinical models, leading to substantial reductions in toxic substrate and improved functional outcomes, including CNS effects.

• AX-2911 achieved approximately 80% reduction in liver lipid droplets with 23% RNA editing, outperforming knockdown strategies and clinical-stage ASOs.

Platform, AI Strategy, and Partnerships

• AI-guided EON design and robotics-enabled high-throughput screening drive rapid, high-efficiency RNA editing candidate discovery, reducing timelines by up to 90%.

• Announced a strategic partnership with Ginkgo Bioworks, including a strategic equity investment, to leverage their autonomous lab for high-throughput data generation and accelerate AI-enabled drug discovery.

• Developed an AI model over the past 18 months to significantly accelerate and improve editing oligonucleotide discovery.

• Established an AI Advisory Board with leaders from AI and techbio fields, including experts from Owkin, NVIDIA, Hugging Face, Leiden University, HCVC, and Kimia Therapeutics.

• The board will advise on best practices and emerging approaches to accelerate drug discovery and optimize Axiomer editing oligonucleotides.