Connect Familial Hypercholesterolemia (FH) genetic variants to real-world phenotypes, biomarkers, and outcomes.
Uncover missed FH patient cases, including those with atypical presentations or not yet defined.
Inform protocol design, patient selection, and regulatory strategy with robust, literature-backed data.
A leading biopharma company set out to advance disease understanding and clinical management for Familial Hypercholesterolemia (FH), focusing on the LDLR gene. FH diagnosis typically requires a combination of positive family history, physical findings such as xanthomas, elevated LDL cholesterol (LDL-C), and the presence of causative variants in LDLR or related genes. However, these strict, combinatorial diagnostic criteria may be too restrictive and risk missing many true FH patients, especially those with incomplete family history, atypical clinical presentations, or variants of uncertain significance (VUS).
As a result, FH is systematically underdiagnosed, which limits patient identification for clinical trials, therapeutic development, and new standards of care. The sponsor needed robust Real World Evidence (RWE) to overcome these barriers and support development and clinical practice, but traditional data sources lacked the patient-level resolution and variant interpretation required for this task.
Genomenon delivered a comprehensive, literature-derived Patient Landscape for FH, synthesizing published evidence from the global scientific literature to provide clinically actionable insights:
Mapping the Real-World Patient Journey: Curated data for over 51,000 FH patients with LDLR variants, assembling the largest clinical cohort of its kind. This included detailed phenotypes, clinical outcomes, and biomarker values (e.g., LDL cholesterol) across ages and presentations.
Comprehensive Variant Classification: Classified all reported LDLR variants, including pathogenic, likely pathogenic, benign, conflicting variants, and VUS.
Clinical Biomarker Integration: Connected variant data to biochemical and clinical outcomes, enabling genetic findings to be tied to real-world clinical actionability, directly supporting clinical trial strategy and patient identification.
AI-Powered, Human-Validated Curation: Scanned over 10 million full-text articles to extract every published LDLR variant and associated FH patient case. All data points are rigorously reviewed and annotated by expert scientists.
Comprehensive & Flexible Data: Delivered a patient landscape that went beyond traditional case reports – integrating variant classification, phenotypic data, biomarker trends, and real-world outcomes for a full, actionable picture of FH heterogeneity.
Regulatory-Grade Transparency: All findings were directly traceable to the primary literature, enabling confident use in clinical development and scientific engagement.
For the sponsor, this meant:
With Genomenon’s literature-derived RWE, the sponsor was able to:
Transform disease understanding: Leverage the world’s largest curated FH cohort to address unmet needs in diagnosis, trial planning, and clinical care.
Support clinical development: Use patient-level, literature-backed evidence to refine inclusion criteria, protocol design, and trial strategy.
Advance clinical practice: Enable more precise identification and management of FH patients with evidence-based, actionable insights.
Uncover hidden patient populations: Identify FH patients overlooked due to incomplete history, atypical signs, or uncertain genetic findings.
Lay groundwork for future therapies: Establish a reusable evidence framework for rare and ultra-rare diseases, accelerating future development programs.
We help provide insights into key genetic drivers of diseases and relevant biomarkers. By working together to understand this data, we enable scientists and researchers to make more informed decisions on programs of interest. To learn more about how we can partner together to find your genomic variant solutions, we invite you to click on the link below.
