PathAI Launches AIM-HER2 Breast Cancer, an Artificial Intelligence-Powered HER2 Scoring Algorithm for Biopharma Research and Clinical Labs
–News Direct–
PathAI, a leading provider of AI-powered pathology tools to advance precision medicine, today announced the availability of AIM-HER2 Breast Cancer [i] for research use by clinical laboratories, researchers, and drug developers. AIM-HER2 Breast Cancer delivers automated digital HER2 scoring and is the markets first algorithm to use additive multiple instance learning (aMIL) heatmaps to visualize the slide features driving the algorithms predicted score. AIM-HER2 will be available to biopharma researchers and clinical research lab pathologists on PathAIs AISightTM [i] digital pathology platform in both the clinical research lab and clinical trial setting.
HER2 IHC assays have provided immense impact to patients by allowing for a widely available test to establish drug eligibility, said Mike Montalto, Chief Scientific Officer at PathAI. With AIM-HER2 Breast Cancer, we at PathAI sought to build upon the success of HER2 testing by assisting pathologists in their ability to more confidently score HER2, especially in borderline cases that can be the most challenging and time consuming to review. We also look forward to partnering with drug developers who may be interested in enhancing the scoring of the more recently described HER2 low assay as an important emerging patient population.
In addition to predicting slide-level HER2 score, AIM-HER2 Breast Cancers visualizations on AISight utilize additive multiple instance learning (aMIL) heatmaps to deliver a more interpretable and explainable prediction, diminishing the black box challenges typically associated with understanding how AI predictions are made.
Our interpretable heatmaps are critical to driving utilization and adoption of AI because its not about blind trust, said Eric Walk, Chief Medical Officer at PathAI. The results can be interpreted, explained and confirmed by humans. It also streamlines workflow as it allows pathologists to hone in on specific features to confirm the algorithm score and output vs. needing to analyze the entire slide.
AIM-HER2 Breast Cancer was developed using 157,000 tissue annotations and consensus scores on a dataset of over 4,000 slides (collected from more than 65 expert breast pathologists). In addition to slide-level HER2 scoring, AIM-HER2 Breast Cancer quantifies invasive carcinoma and provides a comprehensive analysis of the entire WSI without necessitating manual selection of the region of interest (ROI).
To learn more about AIM-HER2 Breast Cancer, register for our webinar on Thursday, July 27, at 11:00am Eastern Time or visit www.PathAI.com
Footnotes
[i] Both AISight and the AIM-HER2 Breast Cancer Algorithm are intended for research-use only. Not for use in diagnostic procedures.
About PathAI
PathAI is the only AI-focused technology company to provide comprehensive precision pathology solutions from wet lab services to algorithm deployment for clinical trials and diagnostic use. Rigorously trained and validated with data from more than 15 million annotations, its AI-powered models can be leveraged to optimize the analysis of patient samples to improve efficiency and accuracy of pathology interpretation, as well as to better gauge therapeutic efficacy and accelerate drug development for complex diseases.
PathAI, which is headquartered in Boston, MA, and operates a CAP/CLIA-certified laboratory in Memphis, TN, is proud to have a team of 600+ innovative thinkers from around the globe. For more information, please visit www.pathai.com.
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