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.
Check out this recent article by American Health Leader (AHL) on how QIAGEN is helping clinical diagnostic and pathology labs adopt genomics-guided precision medicine workflows.
Sean P. Scott, Chief Business Officer and Vice President of Clinical Market Development at QIAGEN, explains QIAGEN’s holistic approach to developing and expanding NGS-based test services. “No matter the size of the lab, we’re focused on helping them understand how to develop a more insightful and actionable report for the ordering physician . . .”
Read the full article here!
QCI Interpret makes precision medicine possible by offering one, cloud-based platform to handle a range of genomic testing, from somatic to germline, from small panels to exome and whole genome.
Get in touch with one of our QCI Interpret experts today!
If you answered yes, we invite you to watch a free recording of our webinar that addresses one of the key bottlenecks of today’s clinical testing laboratory: producing standardized interpretation that is consistent among personnel, reproducible within the testing community, and in accordance with professional guidelines. We show how our clinical NGS reporting and interpretation software, QCI Interpret, not only makes precision medicine possible, but simplifies workflows and increases productivity.
We are proud to share an article written by Ramon Felciano, Chief Technology Officer and Vice President, Strategy & Technology, QIAGEN Bioinformatics, that was featured in The Pathologist, a UK-based publication that considers the latest research and innovation in pathology and diagnostics. Titled “Deciding Factors,” the article shines a light on new trends in clinical labs that are improving the accuracy and efficiency of genetic test interpretation. It argues that these advances are made possible with clinical decision support (CDS) tools, which incorporate big data, sophisticated informatics, and augmented intelligence (as opposed to artificial intelligence), to better inform treatment decisions, manage liability risk, and ensure compliance with ever-changing data privacy regulations.
The adoption and implementation of CDS tools is no longer a luxury, but rather a necessity. Just a few years ago in the United States, only pre-eminent academic medical centers offered precision medicine. As stated in the article, “Today, an estimated 24 percent of hospitals will provide some form of precision medicine by the end of 2018.”(1) With the use of CDS tools and related technologies gaining traction, clinical teams need to ensure they select support tools that provide maximum interpretation transparency and detailed reporting. Dr. Felciano explains how CDS tools are personnel assets—not replacements—that enhance productivity, reliability and the practice of precision medicine.
(1)N. Versel, “Data requirements, money hold back growth of precision medicine among health systems” (2018). Available at: https://bit.ly/2qFSb60. Accessed April 18, 2018.
