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InheriNext

InheriNext is a bioinformatics platform that automates the interpretation of next-generation sequencing data for inherited diseases. It streamlines variant calling and ranking, integrating clinical phenotypes and ACMG guidelines to accelerate diagnostic accuracy and research efficiency.

Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Interpreting and identifying the genetic causes of inherited diseases from next-generation sequencing (NGS) data is a complex and time-consuming process. This complexity can lead to diagnostic delays and hinder research efforts aimed at understanding disease mechanisms.

Solution

InheriNext is a bioinformatics platform designed to streamline the interpretation and discovery of genetic variants associated with inherited diseases. It leverages a proprietary variant ranking algorithm and an intuitive user interface to empower scientists and clinicians. The platform automates the analysis of NGS data, from secondary analysis to variant interpretation, providing transparent reporting with supporting evidence to enhance diagnostic accuracy and research efficiency. By integrating clinical phenotypes, _in silico_ gene panels, and established guidelines like ACMG, InheriNext facilitates faster identification of causative variants and supports collaborative efforts in genetic diagnostics.

Target Audience

The primary users are clinical geneticists, researchers in academic institutions, and diagnostic laboratories that perform NGS analysis for inherited disease diagnosis and research.

Features

  • Automated variant calling and interpretation pipelines supporting FASTQ and VCF formats.
  • Advanced variant ranking algorithm that prioritizes causative variants based on clinical phenotypes, gene panels, and pathogenicity scores.
  • Integrated ACMG guideline support with customizable filtering options for enhanced clinical judgment.
  • Transparent reporting that includes supporting data, triggered ACMG rules, and links to relevant databases (e.g., ClinVar).
  • Rapid turnaround times, with WES analysis completed in as little as 3 minutes and WGS in 15 minutes post-VCF upload.
  • Phenotype Gene Prioritizer module for ranking and interpreting variants based on phenotypic correlation.
  • Workflow Runner for automating the conversion of raw sequencing data into actionable insights.
  • PhenoVarDB (beta) for cohort analysis and community data comparison.
  • Expert module (beta) incorporating Large Language Models for conversational query capabilities in interpretation.
  • US FDA listed as a Class 1 Software as a Medical Device (SaMD).
This profile is AI-generated and may contain inaccuracies.