Insight Molecular Diagnostics (IMDX) KOL event summary

Strategic Focus and Market Approach

• Emphasis on decentralizing dd-cfDNA transplant rejection testing from central labs to local centers for improved patient management and care accessibility.

• Three-pronged market strategy: service lab in Nashville for technology validation, an RUO product for community feedback, and an IVD kit for FDA submission and broader adoption.

• Clinical validation involves a multi-center study targeting 125–150 patients, aiming for FDA submission by year-end and subsequent EU IVDR support.

• U.S. dd-cfDNA transplant testing market is highly concentrated, with two companies holding ~90% share, and over 200,000 tests ordered annually, mostly sent to outside labs.

• Local lab access could expand reach to over 400 U.S. transplant programs and community nephrology practices.

Clinical and Operational Advantages

• Cell-free DNA (cfDNA) testing offers high negative predictive value (~96%), reducing unnecessary biopsies and associated costs, and is now standard of care in transplant monitoring.

• Bringing dd-cfDNA testing in-house reduces turnaround from 5–7 days to same day, enabling faster interventions and improved patient outcomes.

• In-house cfDNA testing addresses logistical challenges of send-out tests, such as long turnaround times and invalidated results, enabling same-day clinical decisions.

• Integration with EMRs and local billing streamlines workflow and creates new revenue opportunities for transplant centers.

• In-house testing offers clinical and operational advantages, supporting broader market penetration.

Clinical Validation and Performance Metrics

• GraftAssureDx trial aims to validate non-inferiority to standard of care using biopsy as reference, with sensitivity target ≥56% and specificity target ≥75%.

• Predictive value thresholds: NPV ≥85%, PPV ≥49% for a 20% a priori probability.

• Primary clinical endpoint is non-inferiority to existing dd-cfDNA tests, with confidence in exceeding current standards based on a decade of published data.

• Large registry studies (COR, ProActive) are informing optimal test cutoffs and use of AI-driven propensity scores to improve predictive accuracy.

• FDA is increasingly accepting surrogate endpoints and longitudinal data, supporting broader surveillance use.