Every year, 350,000 families wait weeks for prenatal test results that never arrive. Our AI-enhanced platform will reduce test failures by 50-70%, enabling earlier answers and greater peace of mind.
Our AI-enhanced platform addresses the fundamental limitations of current NIPT technology, enabling earlier detection and dramatically reducing test failures.
Reliable detection at 4%+ foetal fractions with standard sequencing. Roadmap target: 2% FF with high-depth sequencing (4M+ fragments), enabling testing from 7-8 weeks gestation.
50-70% reduction in test failuresState-of-the-art foundation model trained on unlimited synthetic data, enabling pattern recognition across 100-1000x larger datasets than any real-world collection.
10M+ synthetic samples for trainingResults available 2-3 weeks earlier than current technology. Fewer repeat tests, earlier answers, and reduced anxiety for families during critical decision-making periods.
Testing from 10 weeks (target: 7-8 weeks with high-depth)Actively addressing disparities in prenatal testing. Support for multiple ancestries including European, African, East Asian, South Asian, and Admixed American populations.
Equitable outcomes across all populationsRigorous 4-level validation framework ensuring biological accuracy. All performance metrics validated against real clinical NIPT datasets.
99.9% sensitivity, 99% specificityGenerate unlimited biologically accurate synthetic data without accessing sensitive patient information. Perfect for validation, development, and global deployment.
Zero patient data exposureOur platform combines synthetic data generation with AI foundation models to transform prenatal testing. Here's how the technology works together.
Our 120M parameter conditional causal transformer generates unlimited, biologically accurate synthetic cfDNA sequences at scale—enabling training datasets 100-1000x larger than any real-world collection whilst maintaining perfect ground truth labels.
Extract comprehensive features from real cfDNA: fragment lengths, GC content, positional biases, end motifs, and methylation patterns across diverse populations.
Train the 120M parameter causal transformer on extracted features. The model learns sequence patterns conditioned on fragment length, GC content, and foetal fraction.
The transformer generates sequences token-by-token using learned nucleotide distributions conditioned on target properties, producing realistic cfDNA patterns with perfect ground truth labels.
Generate unlimited synthetic cfDNA samples with specified conditions. Each sample maintains statistical properties matching real clinical data—enabling research and validation at unprecedented scale.
A foundation model trained on unlimited synthetic cfDNA data from our causal transformer. By learning the true biological patterns of cell-free DNA fragmentation, our model achieves breakthrough sensitivity—validated detection at 4%+ foetal fraction, with a roadmap to 2% FF using high-depth sequencing (4M+ fragments).
Validated at 4%+ FF. Roadmap: 2% FF with 4M+ fragments, enabling testing 2-3 weeks earlier in pregnancy.
Trisomies 21/18/13, sex chromosome aneuploidies, microdeletions (22q11, 15q11), triploidy, and rare variants.
Trained on European, African, East Asian, South Asian, and Admixed American population profiles for equitable accuracy.
Synthetic data generation enables training on datasets 100-1000x larger than any real-world collection.
Testing from 10 weeks (target: 7-8 weeks)
50-70% reduction in test failures
Validated at 4%+ FF (target: 2% with high-depth)
Our path from synthetic data generation to transforming prenatal testing globally.
Conditional diffusion model generating biologically accurate cfDNA data across 50+ conditions and 5 populations.
AI foundation model trained on synthetic data, enabling detection at 4%+ foetal fraction (target: 2% with high-depth).
Retrospective validation study with clinical outcomes. ISO 13485 certification.
CE marking submission for UK/EU markets. FDA pre-submission meeting.
CE marking approval and first commercial deployments with laboratory partners in UK/EU.
FDA clearance and US laboratory partnerships. Scale to millions of tests annually.
Our platform supports detection of a comprehensive range of chromosomal abnormalities and monogenic disorders—with synthetic data generation enabling validation for even the rarest conditions.
All conditions include accurate chromosomal dosage effects, proper foetal fraction integration, and validated Z-score detection across diverse populations.
Our platform undergoes a 4-level validation framework ensuring biological accuracy and clinical performance across all use cases.
Real-world benefits for patients and healthcare providers
Whether you're a healthcare provider, researcher, or diagnostic laboratory, we can help you reduce test failures and enable earlier detection.
Offer your patients earlier, more reliable prenatal testing with fewer failures and repeat tests.
Learn MoreAccess unlimited synthetic cfDNA data for developing and validating new algorithms and approaches.
Request DemoIntegrate our foundation model to dramatically reduce test failures and improve turnaround times.
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