SeqOne provides a clinical decision support platform that utilizes AI-driven bioinformatics to analyze next-generation sequencing (NGS) data for germline and somatic variants. The platform enhances diagnostic accuracy and efficiency by identifying complex genomic events that standard pipelines often overlook, thereby improving patient outcomes in precision medicine.
Funding
$26.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
MROCFounders
Product
Problem
Molecular diagnostic labs face challenges in the analysis of next-generation sequencing (NGS) data, including the identification of complex genomic events, maintaining acceptable turnaround times, and ensuring quality control and regulatory compliance. The interpretation of a high number of variants per patient requires expert knowledge and is time-consuming, creating bottlenecks in delivering precision medicine.
Solution
SeqOne provides a clinical decision support platform that leverages AI-driven bioinformatics to streamline and enhance the analysis of NGS data for both germline and somatic variants. The platform identifies hard-to-detect variants, such as MNVs, Alu elements, and mid-sized deletions, that are often overlooked by standard pipelines, improving diagnostic accuracy. SeqOne's DiagAI score ranks variants based on their likelihood of being disease-causing, using machine learning models trained on millions of variants and incorporating phenotypic information. The platform automates variant reevaluation and offers explainable AI to ensure transparency in the decision-making process.
Target Audience
The primary customers are molecular diagnostic labs, human genetics laboratories, and clinical researchers in oncology and rare diseases seeking to improve the efficiency and accuracy of NGS data analysis and deliver personalized medicine.
Features
- AI-powered variant ranking with the DiagAI score, combining pathogenicity, phenotype relevance, inheritance, and quality criteria
- Universal Pathogenicity Predictor (UP²) trained on over 2.5 million variants from ClinVar with 97% accuracy in ACMG variant classification
- PhenoGenius for phenotype-driven genomic analysis, leveraging gene-phenotype associations to rank genes based on patient symptoms
- DiagAI ShortList to generate a concise list of potential causal variants, averaging less than 18 variants for WES with 96% accuracy
- DiagAI SmartPick to suggest the most likely disease-causing variants with 90% specificity
- SomaHRD for genomic instability testing in ovarian cancer, validated against the Myriad myChoice™ test
- GenomeAlert! for automated reevaluation of genetic variant classifications against ClinVar
- Support for various NGS applications, including oncology, inherited diseases, and multi-omics analysis
- Compatibility with Oxford Nanopore sequencing for clinical use
- CGH array interpretation with AI-powered CNV annotation and ACMG classification