When it comes to NGS variant interpretation, content is king. But when your lab’s genomics software platform relies largely on data-sharing and crowdsourced information, how reliable are your reports?
Commercial genomics software platforms support molecular diagnostic workflows by providing unified interfaces connected to selected knowledge bases. These variant interpretation tools take a list of variants and return aggregated information retrieved from individual knowledge bases. This content is then used to filter and prioritize variants and ultimately derive a diagnosis and/or treatment recommendation. Therefore, a lab’s ability to accurately interpret a variant’s biological and clinical significance lies in the strength of its genomics software platform's knowledge base.
In recent years, crowdsourcing has become increasingly prominent as a means of supplementing the data obtained from more traditional sources, such as academic papers and drug labels. Around the world, initiatives and working groups, such as ClinVar, have developed centralized resources where users can submit variants reported in patient samples and assess their significance. Even commercial software companies, such as Sophia Genetics, have created “global data-sharing networks,” enabling their users to upload and share data with other users in the network.
While crowdsourcing is beneficial when it comes to solving challenging cases, there is one inherent issue: crowdsourced data lacks standardization. Clinical laboratories and medical institutions generate patients’ genetic variants through different sequencing protocols and NGS pipelines. This leads to genetic variants that are not interoperable. As a result, data contained in crowdsourced resources is not as reliable as data contained in a standardized, exert-curated knowledge base.
But there is an inherent dilemma: For many molecular diagnostic labs, purchasing a new variant interpretation platform is not option. The question then becomes, how can molecular diagnostic labs fill in the gaps of their crowdsourced data to ensure their variant interpretation is accurate and timely.
QIAGEN Digital Insights offers two proprietary databases that can supplement your lab’s current variant interpretation platform with trusted, expert-curated content.
HGMD Professional remains the largest, manually curated resource for finding disease-causing mutations. Founded and maintained by the Institute of Medical Genetics at Cardiff University, the database attempts to collate all known (published) gene lesions responsible for human inherited disease, giving you the best possible chance of reaching a diagnosis.
Unlike other competitors who offer little to no data curation or overload users with unhelpful literature and volumes of conflicting data, HGMD Professional combines electronic and human search procedures during data curation in order to provide high-quality information. For more than 30 years, a team of expert curators has consistently screened peer-reviewed biomedical literature in over 250 journals to update HGMD Professional.
A research team at Cardiff University updates HGMD Professional quarterly. As of November 2022, HGMD Professional contains over 377,510 detailed mutation reports and more than 11,500 expert-crafted variant summaries of disease-associated/functional polymorphisms. HGMD Professional adds over 45,000 mutation reports per year.
How can HGMD Professional boost your content?
→ Using the public version of HGMD? Your lab does not have access to over 3 years of expert-curated data contained in HGMD Professional. See what else you’re missing here.
The “somatic version” of HGMD Professional, the Human Somatic Mutation Database (HSMD) is a new somatic database developed by QIAGEN that contains extensive genomic content relevant to solid tumors and hematological malignancies. Available as a web-based application, HSMD contains content from over 4.2 million mutations from two sources. Content is curated from over 420,000 real-world clinical oncology cases and the QIAGEN Knowledge Base.
HSMD provides gene-level, alteration-level, and disease-level information, including clinically observed gene and variant frequencies across diseases. Clinically relevant content in HSMD is placed into the perspective of clinical treatments, providing the links between biomarkers and targeted therapies, and is backed up with relevant scientific and clinical evidence. Users can easily search and explore mutational characteristics across genes, synthesize key findings from drug labels, clinical trials, and professional guidelines, and receive detailed annotations for each observed variant. In addition, users can interrogate a bibliography of over 150,000 variant-specific PubMed articles. HSMD also provides access to individual summaries of alteration-type specific information written by PhD scientists.
As QIAGEN Clinical Insights, QIAGEN’s clinical decision support platform for variant analysis, interpretation, and reporting, continues to be adopted by a growing number of molecular diagnostic labs around the world (The platform recently surpassed interpreting over 3 million NGS patient cases worldwide), the data contained in HSMD is increasing at a compounding rate. HSMD adds a minimum of 70,000 new clinical oncology cases each year.
How can HSMD boost your content?
→ Learn how a national cancer research center in Serbia is using HSMD to confidently identify meaningful mutations in somatic tumor testing here.
Explore, search, and test HGMD Professional and HSMD for free. To demonstrate the quality, flexibility, and simplicity of HSMD, QIAGEN Digital Insights offers complimentary, 5-day trials of both expert-curated database. Start your free trial today.
→ Request your free trial of HGMD Professional here.
→ Request your free trial of HSMD here.
With recent announcements of software retirements in the clinical NGS industry, many clinical diagnostic labs are looking for new variant interpretation and reporting platforms to integrate into their current NGS pipelines. With so much competition and seemingly fewer differentiating factors between platforms, it’s hardly surprising when labs are confused and overwhelmed when attempting to choose one software solution over another. Here are five key factors to consider when selecting a new clinical informatics platform.
We understand the challenge of selecting and onboarding a new clinical informatics platform to replace your current software. To aid in your selection process, here are five key factors to consider when choosing a new solution.
When your lab invests in a clinical informatics platform, you want assurance that the commercial provider will support you for the long-term. You need to choose a company and platform that offers experience and stability.
The experience and stability of QCI Interpret and QIAGEN:
Trust and transparency are “buzzword” in the clinical informatics software market. But what do they actually mean?
When it comes to interpreting and reporting clinical NGS tests for patient care, diagnostic labs cannot afford misinterpreting a variant or returning tests week (sometimes days) after they are ordered. You need to return high quality, accurate reports fast. You need clinical NGS variant interpretation and reporting software that you can trust.
Your ability to trust your clinical NGS variant interpretation and reporting software derives from the content that supports the platform. Many commercial platforms provide automatic variant classifications based on clinical practice guidelines (ACMG/AMP, AMP/ASCO/CAP, etc.). However, it’s how these platforms perform these auto-classifications that’s the differentiator.
For example, QCI Interpret, QIAGEN’s clinical informatics platform, provides evidence to trigger all 28 criteria of the ACMG/AMP variant interpretation guidelines. Once a VCF file has been uploaded to the software, within seconds, QCI Interpret returns evidence categorized into one of the 28 defined criteria set forth by the ACMG/AMP guidelines and assigns a calculated strength of the evidence. ACMG classifications automatically include case-level information, such as inheritance models and relevant findings in associated samples, and if additional information or expertise is available, users can incorporate their data, modify criteria, and store changes for all downstream cases. Users can then view each piece of evidence used in the assessment through clickable hyperlinks that show the full article—not the abstract. This approach ensures the software’s automated variant classifications consider all available evidence; but it also gives confidence in the results because it allows users to view the evidence considered. This added layer of transparency gives users full control over final assessments, which is critical in clinical variant interpretation.
This factor coincides with trust and transparency. Curation is a critical component of clinical variant interpretation and reporting. It involves searching through the entire body of medical and scientific knowledge to find the precise information needed to accurately classify and interpret a variant. But with thousands of new articles on human genetic variants being added each week to the over 30 million existing medical articles listed in the National Library of Medicine/MEDLINE/PubMed database, variant curation is a huge bottleneck for clinical diagnostic labs.
To help expedite the process, several commercial informatics providers rely on AI and machine learning to rapidly index the millions of articles to find key pieces of evidence. However, there are significant limitations to pure AI approaches.
Why you can't soley rely on AI:
However, let’s be clear. AI does afford significant efficiencies in variant curation. Therefore, the gold standard approach is to combine AI with manual curation. At QIAGEN Digital Insights, we employ over 100 expert curators (MD and PhD level) who are certified in clinical variant curation. Our curation team uses AI and machine learning to rapidly extract and identify articles. Then, they manually review the AI-extracted content to ensure consistency and accuracy. Using human judgement and expertise, our curation process ensures every catalogued “finding” has been “touched” by a trained scientist. No other commercial provider of clinical informatics platforms can claim this.
View an infographic of our curation process here.
As a clinical diagnostic lab, it’s important to feel supported by your software provider. You need assurance that your provider can support you through onboarding, production, and management. You need a dedicated support team that is responsive and always available to answer questions, trouble shoot problems, and optimize your pipeline.
Each of our QCI Interpret customers receive dedicated localized support from our Field Application Scientist team, who is highly specialized in the field of clinical genetics. You have access to your customer support team at all times and we have the ability to make site visits when needed.
Finally, you need a clinical informatics platform that can be customized to your lab’s unique applications and objectives. QCI Interpret is an agnostic platform that can be paired with any panel or sequencer. Working with your dedicated support team, you can customize your workflows to your panels and reporting needs.
Make the switch to QCI Interpret, the industry's most trusted clinical bioinformatics platform—used to analyze and interpret more than 3.5 million NGS patient test cases worldwide.
Over the last 20 years, molecular analysis of cancers has offered clinicians a growing toolbox for understanding and treating cancer. Next-generation sequencing (NGS) of tumors identifies alterations that can predict sensitivity and resistance to targeted therapies as well as ascribe prognostic and diagnostic significance. As sequencing power and research into cancer-causing mutations have grown, the number of genes on panels has increased.
In 2022, typical panels can detect hundreds of thousands of mutations across several hundred cancer-related genes. In some cases, laboratories perform exome analysis to detect mutations across all ~22,000 genes in the genome. As a result, the burden of variant interpretation has also expanded exponentially.
Numerous clinical decision support (CDS) software and knowledgebases have been developed to assist variant scientists and laboratory directors with the task of variant classification. These private and commercially available systems utilize varying degrees of software automation and manually curated literature to provide variant assessment and therapy matching for clinicians. The body of literature that must be accessed to deliver accurate variant interpretation is vast. As a result, there is debate in the field as to the most accurate and efficient approach.
CDS software leveraging artificial intelligence or natural language processing can index enormous volumes of literature but lack precision in correctly representing complex genomic interactions in association with clinical outcomes. In this context, human curation remains the gold standard. A community crowdsourcing approach allows contribution from many different experts and can help to build a larger pool of knowledge in the context of limited resources.
However, significant standardization efforts are required to ensure a consistent level of accuracy and reliability. In contrast to machine curation, human professional expert curation is resource intensive but can provide consistent and accurate interpretation.
QIAGEN Clinical Insight (QCI) Interpret for Oncology is CDS software that enables pathologists to identify biologically and clinically relevant oncology-related variants. The software draws on a large knowledgebase of curated information, coupled with an expert interpretation service. The content core of QCI Interpret, the QIAGEN Knowledge Base is populated through a combined approach utilizing human and machine curation. Known as augmented molecular intelligence (AMI), this approach combines artificial intelligence and human expertise to advance and accelerate confident clinical decision-making.
A key differentiator of QCI Interpret, the application of AMI leverages artificial intelligence and machine
learning to efficiently identify, extract, and align evidence from scientific literature, guidelines, clinical trials, and drug labels in over 40 public and proprietary databases in the QIAGEN Knowledge Base. This evidence is then reviewed by over 200 PhD- and MDlevel scientists to ensure accuracy, consistency, and
relevance. The evidence is then stored in computable units according to well-defined protocols.
QCI Interpret utilizes the structured content of the QIAGEN Knowledge Base to match appropriate variant- and disease-specific content and executes rules to classify variant pathogenicity and actionability based on the ACMG (1) and AMP (2) guidelines. The computed classification and supporting data are available for review in a user interface. And the user has the ability to review all the data and approve or revise the classification.
QCI Interpret also incorporates an additional level of human expert interpretation. Users can submit variants to the expert interpretation service and oncologists review the clinical content.
The expert interpretation available in QCI Interpret utilizes a contrasting analysis approach; the scientists execute a topic-based analysis, searching for and extracting information on each variant and formulating an assessment based on the synthesis of the evidence. Then, the usesr receives report-ready text with references to incorporate into the final report. Users can easily view the expert classification and interpretation alongside the computed classification, and the user can approve or revise the classification for reporting.
Multiple studies compare variant classification across institutions (3-5). However, these studies lack a “gold standard” set of variant interpretations that could stand as a benchmark for evaluation.
In order to assess the utility and accuracy of QCI Interpret, QIAGEN engaged GenQA, an external quality assessment organization. GenQA designed and executed a study published in the Journal of Molecular Pathology that compared the use of QCI Interpret to internal laboratory methods. The study recruited eight independent laboratories to utilize QCI Interpret for variant interpretation. Variant classification results were compared and an expert panel resolved all conflicts. The results suggest QCI Interpret is a reliable CDS tool that can help laboratories streamline and improve interpretation practices.
Learn more about the study, including how QCI Interpret performed against the 8 laboratories, sources of discrepancies, and methods of variant analysis.
November 1-5, 2022 in Phoenix, Arizona
This year at the Association for Molecular Pathology (AMP) 2022 Annual Meeting, QIAGEN will be showcasing our integrated cancer NGS workflow powered by augmented molecular intelligence (AMI) at Booth #906. The combination of artificial intelligence and human expertise, AMI is an approach unique to QIAGEN. AMI uses machines to rapidly index millions of articles. Then, human curators review and certify the accuracy, relevancy, and consistency of the information pulled.
Learn more and schedule a 1:1 demo here.
