Overcoming Challenges in Hematological Genomic Testing with Advanced AI
This webinar discusses an effort underway at the University of North Carolina Medical Center's to overcome limitations in the hematological genomic testing workflow with artificial intelligence (AI) from Sophia Genetics.
In the first part of this webinar, Dr. Nathan Montgomery of the UNC Medical Center discusses the rigorous evaluation his lab performed to evaluate Sophia Genetics Myeloid Solution against the overall performance of other vendors' solutions.
The Myeloid Solution is a molecular application that bundles Sophia AI with a capture-based target enrichment kit and full access to Sophia DDM platform. The application is designed to accurately characterize the complex mutational landscape of relevant hematological disorders associated with leukemia, myelodysplastic syndromes, and myeloproliferative neoplasms.
Dr. Montgomery first explains the limitations and challenges of the current myeloid test workflow, and the rationale for the group's decision to evaluate other solutions, including the need to perform orthogonal testing of genes with high GC content such as CEBPα. Then, he will lay out the strategy he and his group applied to objectively assess the overall strengths and weaknesses of each technology. Finally, Dr. Montgomery presents his team's conclusions and the reasons they decided to work with Sophia Genetics.
In the second part of this webinar, Dr. Montgomery gives an update on UNC Medical Center's progress with in-house validation and the lab's next steps.
In the last part of the webinar, Dr. Alexander Kurze of Sophia Genetics briefly introduces a solution that will be soon available to test for gene fusions in hematological diseases.