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).
Predicted breakthrough details and their visualizations can be found on the landing page, and are aimed to be raise awareness on a health observance for that month. Links to the papers which are part of this predicted breakthrough are also available.
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 specifically 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 on RCR here.
For the above example, 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 therapy. 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 progression-free survival and overall survival in patients with HER2-low metastatic breast cancer. (Access the publications here.)
Disclaimer: NIH tracks outputs from investigators such as publications and clinical trials. Analytics links grants to publications and individuals through both SPIRES and disambiguation. Linking does not infer an intellectual property connection between publications and awards.