Congenica Automation Further Accelerates Identification of Genetic Diseases

Cambridge, United Kingdom – 15 July 2020 - Congenica has launched Congenica Automation, an update for its clinical decision support platform that will provide automated classification, evidence and reporting of recurrent ‘known’ variants that customers observe in their rare disease cases, significantly saving time while maximizing diagnostic yield and laboratory throughput.

The key to realizing the potential of precision medicine relies on accurate and efficient diagnosis. However, even less complex cases can take experts 11-12 hours using standard tools and workflows – adding over $500 of staffing cost to every analysis.[1] Congenica already reduces the working time for interpretation and reporting by 90%, but the launch of the new Automated Classification of Known Variants capability reduces time to report by an additional 90% - enabling complex genomic data interpretation and reporting in as little as 5 minutes. The flexibility of Congenica allows users to create their own customized curated variant list to be used for the automated process such as recurrent variants common to their test protocols.

In a study analyzing 19,000 cases from the Congenica Knowledgebase a team of Registered Clinical Scientists identified nearly 4,000 cases with recurrent pathogenic or likely pathogenic variants, which Congenica Automation would have automatically classified, thereby increasing throughput significantly. Using the Congenica Automated Classification of Known Variants pipeline, interpretation and reporting of each of these 4,000 cases could be completed in 5-8 minutes, saving almost 5,500 hours (91%) of combined interpretation effort and 98% of staff costs during interpretation.

The availability of expert qualified staff in genetic analysis departments is currently a significant roadblock to accessing genetic services with 71% of clinical laboratories reporting that they are nearly or completely at capacity.[2] Increasing case throughput and reducing interpretation time are therefore essential.

Prior to this release, Congenica’s core software already enabled rapid evidenced analysis and high throughput of complex genomic cases.[3] With Congenica Automation, it is estimated that labs can increase their throughput and capacity by a further 65%, depending on the frequency of recurrent variants in their cases. This allows for quicker report turnarounds and the ability to process significantly more tests, returning more results in a shorter timeframe while increasing confidence by leveraging clinically verified variant information.

Congenica also now enables customers to access the most comprehensive suite of Splicing Variant Tools on the market, which exceed the ACGS best-practice requirements; make automatic ACMG Score-based pathogenicity calculations; and automatically identify relevant evidence to support interpretation from over 7.5 million publications. This means less work and more results, reducing interpretation burdens while increasing analytic capacity for laboratories and allowing experts to focus their time on the most urgent and complex cases.

Congenica software is used throughout the UK NHS as the exclusive rare disease clinical decision support platform for the first-in-the-world national Genomic Medicine Service and internationally by private and public hospitals and laboratories, where the software reduces average interpretation costs by up to 95% and helps healthcare professionals obtain genetic information 20-times faster than previously possible.

Dr David Atkins, Chief Executive Officer, Congenica: “Congenica Automation functionality further leverages our clinical expertise, extending our platform’s extensive automation capabilities to maximize the efficiency of research into genomic diseases.”

“Where once genomic analysis of these complex cases was incredibly challenging, even for specialists, Congenica Automation provides professionals with a complete bioinformatics solution enabling faster, simplified and reliable variant identification, review and reporting to deliver actionable insights and life-changing answers at scale.”

 

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References

  1. Schwarze, K. et al. Genet Med 22, 85–94 (2020)
  2. Maiese, D. et al. Genet Med 21, 1874–1877 (2019)
  3. White Paper: Analyze, Interpret and Report NGS Data Faster than Ever Before – www.congenica.com/efficiency

 

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