EabhaSeq

AI-Enhanced Prenatal Testing for Earlier, Safer Detection
Backed by Emergent Ventures

Mission

We're revolutionizing prenatal care by using AI to detect fetal DNA signals at ultra-low concentrations, reducing test failures by 50-70% and enabling testing as early as 6-7 weeks. Our platform-agnostic AI integrates with existing lab systems, enabling global adoption. The synthetic data generation model will be open-source, ensuring access to advanced genomic research tools.

Impact

• Reduce prenatal test failures by 50-70%, saving £70M annually in healthcare costs.
• Enable testing at 6-7 weeks, transforming prenatal care globally.
• Ensure equitable genetic screening across diverse populations.

Phase 1: Synthetic Data Foundation

• Generate biologically accurate synthetic cfDNA datasets.
• Simulate maternal and fetal DNA with population-specific patterns.
• Validate against published NIPT datasets for accuracy.

Phase 2: Real Data Validation

• Integrate NHS failed test samples for real-world validation.
• Develop AI algorithms to enhance fetal fraction detection.
• Target significant reduction in test failures.

Phase 3: Production Optimization

• Optimize 100M parameter model for real-time clinical use.
• Develop API for lab integration and clinical reporting.
• Enable screening for 50+ genetic conditions with high accuracy.

About EabhaSeq

Founded by Kyle Redelinghuys, a software engineer with expertise in AI and genomics, EabhaSeq was born from a personal loss to transform prenatal care. With unique NHS Genomics Institute access and the latest advancements in AI, we’re building an open-source synthetic data model to enable earlier, more equitable genetic testing worldwide.