Beta Intercept™ Validation
Analytical Performance. Clinical Evidence. Scientific Confidence.
The Beta Intercept™ program is being developed through a comprehensive analytical and clinical validation framework designed to establish the performance, reproducibility, and biological relevance of beta-cell-derived molecular biomarkers.
Section 01
Validation at a Glance
Six pillars of scientific rigor advancing in parallel across the Beta Intercept™ program.
Analytical Validation
- Assay performance
- Precision
- Sensitivity
- Specificity
Clinical Validation
- Prospective studies
- Longitudinal monitoring
- Pediatric cohorts
- Adult cohorts
Scientific Publications
- Peer-reviewed manuscripts
- Conference presentations
- Scientific posters
Academic Partnerships
- Leading research institutions
- Clinical collaborators
Regulatory Strategy
- Analytical validation
- Clinical validation
- FDA planning
Commercial Readiness
- CLIA laboratory
- Quality systems
- LIS integration
- Clinical reporting
Section 02
Analytical Performance
A regulatory-grade dashboard of pre-specified performance dimensions.
Accuracy
High analytical agreement with reference measurements.
Precision
- Intra-run reproducibility
- Inter-run reproducibility
- Operator reproducibility
- Instrument reproducibility
Sensitivity
Quantitative detection of low-abundance beta-cell-derived cell-free DNA.
Specificity
Tissue-specific methylation biomarkers designed to distinguish pancreatic beta-cell DNA from other circulating cell-free DNA.
Linearity
Validated quantitative performance across the assay's working range.
Sample Stability
Blood collection and processing protocols optimized to preserve cell-free DNA integrity.
Section 03
Clinical Validation Program
Discovery
Analytical Validation
Clinical Validation
Clinical Utility
Regulatory Strategy
Commercial Deployment
Pediatric Type 1 Diabetes
- Longitudinal monitoring
- Autoantibody comparison
- Disease progression
Adult Metabolic Disease
- Prediabetes
- Type 2 Diabetes
- GLP-1 monitoring
- Metabolic dysfunction
Longitudinal Studies
Repeated molecular monitoring over time.
Translational Research
Correlation between beta-cell biology and clinical outcomes.
Section 04
Biomarker Validation
A multi-layered molecular substrate combining tissue-specific DNA signals, autoimmune markers, and clinical chemistry — unified by AI.
Beta-Cell-Derived Cell-Free DNA
Primary indicator of beta-cell injury.
DNA Methylation
Pancreatic tissue specificity.
Autoantibodies (T1D)
Integrated biological assessment for autoimmune disease.
Clinical Biomarkers
AI Molecular Risk Modeling
Integration of multiple biological signals into disease-specific algorithms.
Section 05
Scientific Evidence
Publications
Peer-reviewed manuscripts supporting beta-cell biology and molecular diagnostics.
Conference Presentations
National scientific meetings.
Research Collaborations
Academic institutions.
Intellectual Property
- Patents
- Trade secrets
- Novel molecular biomarkers
Section 06
Clinical Performance Dashboard
Validated performance dimensions, displayed as a live regulatory-grade snapshot.
Precision
Coefficient of Variation
Within validated performance specifications
Analytical Sensitivity
Low-copy detection
Validated detection of low-copy beta-cell cfDNA
Analytical Specificity
Tissue-specific
Tissue-specific methylation markers
Quantitative Range
Working range
Validated working range
Sample Processing
Standardized
Standardized laboratory workflow
Quality Controls
Every run
Built into every analytical run
Section 07
Validation Across Disease Programs
Beta Intercept™ T1D
Applications
- Early detection
- Disease monitoring
- Autoimmune beta-cell injury
- Research
- Clinical trials
Beta Intercept™ T2D
Applications
- Prediabetes
- Metabolic dysfunction
- GLP-1 monitoring
- Therapeutic response
- Population screening
Section 08
Scientific Validation Framework
Beta Intercept™ is continuously strengthened through ongoing research and clinical evidence.
Biological Discovery
Biomarker Identification
Analytical Validation
Clinical Validation
Clinical Utility
Commercial Deployment
Real-World Evidence
Improved Algorithms
Section 09
Measuring Disease at the Cellular Level
Beta Intercept™ is designed to detect molecular evidence of pancreatic beta-cell injury before traditional markers of metabolic dysfunction fully manifest. By combining tissue-specific cell-free DNA analysis, multi-omic biomarker integration, and artificial intelligence, the platform aims to provide clinicians and researchers with earlier, biologically meaningful insights into disease onset and progression.
Headline performance across every validation pillar.
CLIA / CAP / NYSDOH · Method comparison vs. orthogonal ddPCR
0.5 – 5,000 cp/µL
95% probability · Probit
T1D vs. control · n = 1,847
Across 28 days · 4 operators
At calibrated cutoff
At calibrated cutoff
Eight pre-defined acceptance criteria. All met or exceeded.
The InterceptIQ™ assay was validated in accordance with CLSI guidance and internal protocols developed for regulatory submission. Acceptance criteria were pre-specified before unblinding to preserve statistical integrity.
Accuracy
Bias < 2% across operating range
Precision
Inter-run CV 1.6% – 5.4%
Linearity
R² = 0.9999 · 4-log dynamic range
Specificity
No cross-reactivity in 96-sample panel
Recovery
98.1% – 102.4% spike recovery
Stability
≥ 7 days · plasma at 4 °C
Limit of Detection
4.5 copies / µL · 95% Probit
Reference Range
Established across 3 cohorts (n = 1,847)
Linearity, precision, and limit of detection — measured at scale.
Analytical linearity
R² = 0.9999 · 0.5 → 5,000 copies / µL
Precision · inter-run CV
CV < 6% across operating range
Limit of detection · Probit
LoD95 = 4.5 copies / µL
Diagnostic performance · ROC
AUC = 0.979 · T1D vs. control
Established stratification across healthy, at-risk, and active cohorts.
Reference ranges were established prospectively across three IRB-approved cohorts with longitudinal sampling. The calibrated cutoff yields 94.6% sensitivity and 97.8% specificity at the operating point.
Clinical reference ranges
Stratification across cohorts (n = 1,847)
Three independent epigenetic signals.
One calibrated intelligence score.
Rather than relying on a single biomarker, InterceptIQ™ interrogates multiple tissue-specific methylation loci across the insulin gene. The joint signal raises specificity, lowers false-positive rate, and produces a clinically interpretable disease intelligence output.
Open chromatin in pancreatic β-cells; hypermethylated in non-β tissue.
β-cell specific demethylation; conserved across human islet donors.
Independent confirmatory locus; lowers false-positive rate vs. single-site assays.
Calibrated weighted combination — auditable, interpretable, and reproducible across cohorts.
Reproducibility is part of the product.
Pre-registered protocols
Acceptance criteria, statistical analysis plans, and stopping rules are pre-registered before sample analysis.
Containerized pipelines
Every analytical run executes inside a versioned, hash-pinned container, enabling third-party re-execution.
Orthogonal confirmation
Methylation calls are cross-validated against ddPCR and an independent whole-genome bisulfite reference.
Open methods
Sequencing chemistry, basecaller version, and reference atlas builds are documented in the Publication Center.