Delivered patient and variant landscapes far more comprehensive than previously available for ENPP1 Deficiency, directly supporting inclusion/exclusion criteria, endpoint definition, and recruitment projections.
Provided transparent, reference-cited evidence on ENPP1 prevalence, natural history, and unmet need, which strengthened the case for targeted therapeutics and clinical trial feasibility.
Leveraged Real World Insights to illuminate phenotypic variability, high-prevalence subpopulations, and age-dependent disease transitions, informing strategic trial site selection and biomarker planning.
Inozyme Pharma was developing INZ-701, the first therapy to be investigated in clinical trials for ENPP1 Deficiency, an ultra-rare mineralization disorder caused by pathogenic variants in the ENPP1 gene. The disease can present in infancy as Generalized Arterial Calcification of Infancy (GACI), with a mortality rate of approximately 50% in the first months of life, or later in childhood as Autosomal Recessive Hypophosphatemic Rickets Type 2 (ARHR2), with lifelong skeletal and systemic complications.
Designing an effective trial for such a heterogeneous and severe disease requires a depth of understanding around the full spectrum of ENPP1 variants, patient phenotypes, natural history, and prevalence. Public resources such as ClinVar and Orphanet were insufficient for trial planning-many variants were poorly characterized, patient-level data was sparse, and prevalence estimates were outdated and skewed toward overrepresented populations in genomic databases.
Without comprehensive, validated evidence, Inozyme faced the risk of underestimating eligible patient numbers, misaligning inclusion criteria, and overlooking high-prevalence populations that could improve recruitment.
Genomenon partnered with Inozyme to deliver a robust, literature-derived RWE package that included a Variant Landscape, Patient Landscape, and refined Prevalence Analysis for ENPP1 Deficiency. This dataset was further enhanced with Real World Insights to deepen disease understanding and strengthen trial strategy.
Variant Landscape: 109 unique ENPP1 variants were extracted, normalized, and classified using ACMG/AMP guidelines. Genomenon identified dozens of pathogenic or likely pathogenic variants absent from ClinVar, expanding Inozyme’s view of potential trial-eligible mutations. Clusters of pathogenic variants were mapped to key protein domains, and genotype–phenotype associations were highlighted to guide endpoint and subgroup planning. These findings were then submitted to ClinVar to increase access to these insights for the global research community.
Patient Landscape: Clinical data from 154 published ENPP1 Deficiency patients-sourced from literature, natural history studies - including two NHS datasets - were curated and annotated to include demographics, phenotypes, clinical outcomes, interventions, and lab values. Uniquely, patients with longitudinal follow-up were flagged, enabling an understanding of age-dependent disease progression (e.g., GACI in infancy evolving to ARHR2 in childhood).
Prevalence Analysis: Genomenon applied a Hardy–Weinberg equilibrium model adjusted for ethnicity based allele frequency differences, enabling recalculation of ENPP1 Deficiency prevalence across subpopulations and producing estimates that more accurately reflect genetic diversity.” The analysis revealed significantly higher prevalence in EastAsian cohorts compared to global averages. These findings informed trial site prioritization and global recruitment forecasts.
Real World Insights: Beyond trial feasibility metrics, Genomenon mapped phenotypic heterogeneity, natural history milestones, and high-prevalence genotype clusters. This allowed Inozyme to consider early, biomarker-based endpoints in addition to survival and to anticipate age-stratified treatment effects.
AI-Powered, Human-Validated Curation: Genomenon’s AI platform rapidly identified and extracted ENPP1 variants and associated patient data from over 2,300 publications. Genomenon’s team of expert scientists reviewed the data for accuracy, ensuring every variant classification and phenotype annotation was reference-cited and trial-ready.
Comprehensive & Flexible Data: Inozyme’s trial planning required both breadth and granularity. Genomenon delivered structured datasets suitable for clinical protocol development and regulatory submission, supporting both operational and strategic decision-making.
Integrated Disease Understanding and Scientific Partnership: By combining variant and patient RWE with Real World Insights, Genomenon delivered far more than a static dataset. The engagement functioned as an extension of Inozyme’s scientific team — with ongoing consultations, data reviews, and collaborative discussions informing trial design and regulatory positioning.
Genomenon worked closely with Inozyme’s clinical and regulatory leaders to interpret findings, refine protocol assumptions, and shape messaging for external stakeholders. This included joint publications, conference presentations, and scientific briefings that not only validated the RWE but also built credibility with regulators, investigators, and the broader scientific community.
The result was a unified evidence base ensuring the science was both rigorous and effectively translated into trial design, regulatory submissions, and investor engagement.
“Genomenon’s innovative approach to leveraging literature for real-world evidence significantly enhanced our understanding of ENPP1 Deficiency. The data they extracted and the evidence they gathered, not only deepened our knowledge of the disease landscape but also informed our strategic investment decisions, underscoring the power of real-world data in shaping market strategies for rare diseases.”
Catherine Nester, Senior Vice President, HCP and Patient Engagement at Inozyme Pharma
Years of research time saved: The engagement replaced years of internal research effort with a comprehensive, trial-ready dataset, accelerating trial readiness and reducing operational risk.
Strengthened variant evidence base: Expanded the number of recognized pathogenic/likely pathogenic variants by more than threefold compared to public databases, providing Inozyme with a far more comprehensive and defensible dataset for regulatory and clinical trial planning.
Smarter recruitment strategy: Delivered refined, ethnicity-adjusted prevalence estimates, identifying high-prevalence subpopulations for targeted site activation and improving recruitment efficiency.
Endpoint and biomarker optimization: Provided a longitudinally informed patient landscape with genotype–phenotype correlations, enabling endpoint selection and biomarker planning tailored to multiple disease stages.
Regulatory and investor confidence: Equipped Inozyme with transparent, reference-cited evidence that strengthened regulatory submissions and investor engagement, supporting the strategic and scientific case for INZ-701.
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