Overview
OPA recently developed and validated an AI algorithm that scans more than 35 million publications and detects topics predicted to produce a transformative breakthrough in biomedicine within the next two to twelve years (patent pending).
In the videos, you see representations of the topic from when research began to the realization of the breakthrough as well as the clinical impact of the topic.
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In recognition of Breast Cancer Awareness Month in October, we highlighted one of the topics identified in a past run of the AI algorithm.
These papers explore the clinical and molecular features of HER2-low breast cancer, assess the efficacy of HER2-directed therapies, and reveal new opportunities in HER2 testing and therapeutic development. They highlight the potential targetability of HER2-low cancers and evaluate the use of novel antibody-drug conjugates, such as trastuzumab deruxtecan (T-DXd), in improving overall and progression-free survival in patients with HER2-low metastatic breast cancer.
Overall, the animation shows the number of papers about HER-2 low breast cancer published from 2009-2022. The number of papers increases steadily from 2018 onward. A citation network also shows how publications become increasingly cited and clinically-focused beginning in 2018.
The blue bars represent the sum of the RCR values for the papers in each year. If the sum of RCR is equal to the number of papers, then they are being cited the same as the NIH average (1.0). If it's greater than the number of papers, then the portfolio is more influential. Learn more about RCR.
See the landing page of iSearch Analytics for the current highlighted breakthrough.