QCI Interpret's latest software update comes with several new features, including a new workflow for comprehensive cancer panels and greater variant coverage for labs using the GRCh38 reference genome
We are pleased to announce that the Summer 2022 Release of QCI Interpret, QIAGEN’s decision support software platform for the annotation, classification, and reporting of actionable alterations from next-generation sequencing (NGS) data in clinical genomic laboratories, is now available. Expanding on the software’s current capabilities, the QCI Interpret Summer 2022 Release brings new workflows, variant content and functionality improvements.
QCI Interpret is a clinical decision support software platform for the annotation, classification, and reporting of actionable alterations from NGS data for oncology and hereditary disease applications. Using augmented molecular intelligence and expertly curated content from the QIAGEN Knowledge Base, QCI Interpret applies a rules-based approach to automatically compute pathogenicity classifications (Pathogenic to Benign) and actionability classifications (Tier 1 to 4) for each alteration according to professional guidelines from ACMG/AMP and AMP/ASCO/CAP, respectively.
Pathogenicity and actionability classifications in QCI Interpret are accompanied by clear visibility into the criteria and evidence supporting the classifications. This workflow starts with a variant call format (VCF) file, so it is compatible with the output from any NGS platform. The final report includes the alterations, interpretations, and references specified throughout the assessment process, which has customizable automation capabilities allowing for streamlined clinical decision support workflows.
Learn more about QCI Interpret for Oncology here.
Learn more about QCI Interpret for Hereditary Diseases here.
We are pleased to announce that the latest QIAGEN Clinical Insight (QCI) Interpret software release is now available. Expanding on the software’s current capabilities, the update adds new features and guidelines to enhance the interpretation and reporting of genomic variants.
Immediately determine and filter to genes implicated in hereditary diseases that are most relevant to report with Strong or Definitive Clinical Validity. With this new features, users can quickly review clinical validity statements that summarize the evidence supporting the strength of a gene-disease relationship. Gene-disease relationships include those determined by the ClinGen Gene Curation Working Group and are extended to cover all gene-diseases via computing clinical validity based on the ClinGen classification guidelines using the expert-curated and integrated evidence in the QIAGEN Knowledge Base.
Interactively add and remove symptoms (and diseases) in hereditary workflows at anytime. With this new feature, users can rapidly adjust symptoms if more case information becomes available. The ranking of candidate diseases for variants in the Phenotype Driven Ranking (PDR) view is dynamically updated based on the updated symptoms.
Review curated evidence supporting each candidate disease for a case in the hereditary workflow with the Phenotype Network—a new feature that provides a summary of the gene-disease clinical validity and a visual diagram of the paths via QIAGEN Knowledge Base relationships from symptoms provided for a case to a candidate disease. This enables users to quickly and interactively review relationship-specific supporting evidence, including source citations.
The NICE Guidelines for Oncology are now available for clinical reporting in QCI Interpret and QCI Interpret One. QIAGEN’s expert guideline curation provides the most up-to-date evidence-based guidance from NICE to support treatment selection for patients. NICE guideline recommendations are also used to support the computed AMP/ASCO/CAP variant classification to ensure relevant variants are indicated for review.
For information about the latest release, including the full release notes, please contact your QIAGEN Digital Insights account manager or customer support at ts-bioinformatics@qiagen.com.
We also invite you to watch our on-demand webinar, "Overcoming Challenges of Copy Number Variant (CNV) Interpretation," where our experts provide a virtual demonstration of QCI Interpret, showing how users can quickly evaluate CNVs and compute their pathogenicity using the new ACMG/ClinGen guidelines.
Visit our QCI Interpret webpage to request a complimentary demonstration.
We're pleased to announce that our newest clinical NGS variant interpretation and reporting solution is now available in Europe.
QCI Interpret One is clinical decision support software integrated with professional variant interpretation services that enables rapid, evidence-based reporting of oncology NGS tests at scale.
Connected to the world’s most comprehensive, manually curated knowledge base that is updated weekly, QCI Interpret One dynamically computes variant classifications according to AMP/ASCO/CAP and ACMG/AMP guidelines with full transparency.
Users get access to over 200,000 pre-formulated, oncologist-reviewed variant interpretation summaries and can build customizable, oncologist-ready reports with the latest diagnostic and prognostic information, as well as biomarker-directed therapies and regional clinical trials, based on the lab's regional labels and guidelines.
For US users, QCI Interpret One generates reports according to FDA/NCCN/WHO guidelines for therapeutic, prognostic, and diagnostic actionability. View Sample Report.
For EMEA users, QCI Interpret One generates reports according to EMA/ESMO/ELN/WHO guidelines for therapeutic, prognostic, and diagnostic actionability. View Sample Report.
Learn more about QCI Interpret One in our upcoming live webinar, Thursday, October 15 at 10 AM EST | 4 PM CET. Our experts will provide an overview of the solution, as well as demonstrate how QCI Interpret One can help clinical laboratories grow caseload volume, accelerate test turnaround time, and deliver oncologist-ready reports without requiring additional staff.
The contest was called to address a current industry challenge: standardizing variant interpretation and reporting. The increasing demand for next-generation sequencing (NGS)-based tests has led to a high degree of variability in how members of the global molecular genetics and pathology community classify variants and prepare final reports. To better understand the limitations of standardization and move forward in the same direction, Agilent Technologies, Thermo Fisher Scientific, and QIAGEN engaged in a friendly competition to determine which company had the most accurate and consistent NGS analysis and interpretation platform: the Alissa Interpret platform, Ion Torrent platform, and QIAGEN's Biomedical Genomics Workbench and QIAGEN Clinical Insight (QCI™) Interpret, respectively.
Erasmus University Medical Center (Erasmus MC) Rotterdam generated sequence data from five clinical samples using Thermo Fisher’s Ion Torrent platform. The three contestants were given this sequence data and instructed to identify clonal and subclonal mutations in the tumors down to an allele frequency level of at least five percent. Then, the contestants were asked to identify and annotate the variants, calculate allele frequency, and interpret the variants according to a five-tier classification system ranging from “benign” to “clinically significant.”
This was no easy task.
Initially, seven companies expressed interest in meeting the challenge. In the end, only three crossed the finish line. According to Professor Winand Dinjens, the organizer of this year’s competition, and head of molecular diagnostics in the Department of Pathology at Erasmus MC Rotterdam, most contenders dropped out after struggling to analyze the sequencing data, which was produced with the Ion S5 XL System, a version of the Ion Torrent platform. As the race unfolded, unfamiliarity with the provided sequencing data caused more than half of the competitors to exit the track.
So, was there a home advantage?
The sequencing data in question was produced by the Ion Torrent platform, which means the Thermo Fisher team analyzed the data using tools custom-built to work with this type of sequence data. For example, during the variant calling process, the Thermo Fisher team was able to apply “flow space” information for each base as it related to Ion Torrent chemistry.
Even so, QIAGEN didn’t back down.
While Thermo Fisher may have had greater familiarity with this particular “track,” QIAGEN’s bioinformatics solutions are open platforms and have experienced over 750,000 “races” on all types of “tracks” across the world. The QIAGEN Knowledge Base is the industry’s largest, most up-to-date clinical database with the direct experience of analyzing over 750,000 human samples. This cumulative experience, in addition to more than 16 million knowledge base findings across 23,000 genes, gives QCI Interpret greater scope and depth.
For each of the five cancer samples, Erasmus supplied FASTQ files plus aligned BAM files, from which the task was to perform variant calling and interpretation and to generate a list of clinically reportable findings. Tim Bonnert, QIAGEN’s Associate Director of Bioinformatics Field Application Scientists, EMEA first used QIAGEN’s Biomedical Genomics Workbench to process the FASTQ files and perform the variant calling. Then he assessed the variants with QCI Interpret, which has curated content that triggered built-in ACMG/AMP and AMP/ASCO/CAP guidelines.
When the results from all contenders were in, none were identical.
QIAGEN’s software solutions performed significantly better than the competition. The organizers stated that there were a total of 12 variants across the five samples. QIAGEN reported 11 of the 12 variants; the variant had been identified in a homopolymer region, and the QIAGEN team identified this variant as a potential false positive. However, this classification does not change the overall clinical actionability recommendation for the patient. By contrast, Agilent and Thermo Fisher missed multiple calls. In some cases, neither platform detected variants in a sample that did in fact have clinically actionable findings; for example, the Torrent Variant Caller pipeline generated no calls for three clinically meaningful variants.
Even though QIAGEN outperformed competitors and achieved almost 100% concordance, these kinds of “battles” illustrate the importance of having pre-defined and clear standards for bioinformatics workflows. Classification and reporting of variants to healthcare providers is critical for patient care. This process requires: accurate reporting of the tumor response to targeted therapy; establishment of professional guidelines for patient care; and collaborative institutional clinical trials, thereby supporting the need for standardization among laboratories performing these tests.
According to Bonnert, “While Erasmus MC no doubt had these standards nailed down in their routine testing pipelines, for this competition there was, for example, uncertainty about required depth of coverage, acceptable distance into the intron, and other confidence metrics and standards that we believe are essential to any routine clinical bioinformatics approach. The need for standards in routine testing also extends to employing clearly defined rules and assessment criteria supported by curated clinical evidence.”
Standards are important for ensuring consistency of secondary and tertiary analysis workflows and for generating actionable data. The faithful detection of variants from Ion Torrent data by the Biomedical Genomics Workbench and the standardized clinical decision support provided by QCI Interpret proved the winning combination.
We are honored to have participated in the Battle of the Bioinformatics Pipelines. Here at QIAGEN, we are committed to building the most reliable, robust and technologically-advanced bioinformatics tools that are sequencer-agnostic because we want to empower more labs, more clinicians, and more patients to do and know more. Just as our pipeline proved victorious with Ion Torrent data in this battle, our research and clinical solutions work successfully with QIAGEN’s own GeneReader platform, as well as with data from Illumina.
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