Bioinformatics and disease: A growing relationship

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QIAGEN Digital Insights

Bioinformatics and disease: A growing relationship

Recently the Journal of Precision Medicine ran a compelling article by Valentin Barsan, MD, about the increasing relevance of next-generation sequencing (NGS) to evidence-based, point-of-care clinical decision-making. With the many variables within any diagnosis and treatment plan, Barsan asserts that “actionable NGS reporting must therefore convey the analytic and clinical nuances of results so that reports are not misinterpreted as diagnostic finality when truth depends on a plurality of measurements.” This is a noble goal, attainable only by filtering the glut of multi-modal data through a comprehensive platform. While we agree with the article’s premise, we think a stronger case should be made for powerful NGS data analysis solutions that can distill NGS results today into diagnoses and treatment plans.

NGS is a game-changing approach to medicine; combined with high-quality interpretation and analysis powered by manually curated scientific literature and clinical evidence, it will truly advance the diagnosis and treatment of patients. Some of the earliest successes we’ve seen for applying NGS in healthcare come from the cancer field, and our bioinformatics solution for clinical labs targets somatic and hereditary oncology cases. QIAGEN Clinical Insight (QCI) is a secure web application that classifies variants, identifies treatment options, and performs geographic clinical trial matching. QCI’s evidence-based approach evaluates genomic variants against more than 10 million relevant biomedical findings, professional association guidelines, publicly available databases and annotations, drug labels, and clinical trials. It also integrates with the Allele Frequency Community, the world’s largest repository of ancestral and ethnic diversity data.

QCI focus on accelerating insights and the tool allows medical teams to rapidly home in on actionable variants to improve treatment and clinical-trial matching. It also makes it possible to build private, experience-based databases with each variant assessed and reported to increase the speed and accuracy of subsequent interpretations. With QCI, clinical labs can consolidate all parts of the variant interpretation and reporting process while saving time and zeroing in on clinically relevant data. To Barsan’s point — the many complexities of disease must be unraveled, analyzed and integrated before diagnosis and treatment can be fully realized; we believe that a powerful bioinformatics solution will be critical to achieving this vision.

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